Western AAAE Research Conference Proceedings

Transcription

Western AAAE Research Conference
Proceedings
2011
Volume 30
April 20-23
Fresno, CA
Research Conference Chairs
Mollie Aschenbrener
California State University, Chico
Ann DeLay
California Polytechnic State University
Poster Chair
Edward Franklin
University of Arizona
2011 Western AAAE Research Conference
Research Paper Review Process
The 2011 Western AAAE Research Conference Paper Call was disseminated at the 2010
Western Region AAAE Conference in Great Falls, MT. The call was revised, based on the
publication of APA 6th Edition, and re-disseminated through the AAAE list serve and the AAAE
website in October 2010. Paper submission deadline was December 20, 2011.
The 2011 Western AAAE Research Conference received 41 papers from researchers and
authors. Personal identifiers were removed from research papers prior to reviewer assignments
through the FastTrack system. Authors were notified of paper acceptance following the six week
review process. Each paper was blind-reviewed by a minimum of three individuals registered
within the FastTrack system as reviewers.
Reviewers rated the papers on the 69 point scale of the system and noted a level of
agreement/disagreement for acceptance. Once received, review data were coded and analyzed.
Based on the AAAE system, the aggregated point‘s z score was one-third of the final paper score
and the aggregated rating z score was two-thirds of the final paper score. The 27 papers with the
highest final z scores were selected for presentation at the 2011 Conference. The acceptance rate
was 66%. during Authors were notified of their acceptance or rejection status during the first
week of February.
Our sincere appreciation to Dr. David Doerfert at Texas Tech University for providing technical
assistance and facilitating the FastTrack system. Additionally, Dr. Doerfert provided the
spreadsheet template for scoring the reviewed papers.
Additionally, we wish to express our sincere appreciation to Mike Spiess, CSU Chico, for his
leadership and guidance in formulating the conference. The conference would not have been
possible without the coordination provided by Mr. Jim Aschwanden, executive director of
California Agricultural Teachers Association and Mrs. Kerry Stockton, administrative assistance,
California Agricultural Teachers Association.
A special thank you to the session chairs and facilitators of the nine research sessions at the 2011
Western AAAE Research Conference. Finally, thank you to the authors who graciously shared
their research to strengthen our profession.
April 20-23, 2011
2011 Western AAAE Research Paper Reviewers
Thank you to the professionals listed below who volunteered their time and expertise in the
paper review process.
Adam Kantrovich
Alyx Shultz
Amy Harder
Billye Foster
Brad Greiman
Brian McCann
Brian Myers
Brian Parr
Chris Morgan
Craig Edwards
Daniel Foster
David Jones
Deborah Boone
Don Edgar
Don Johnson
Ed Osborne
Elizabeth Wilson
Gary Briers
Grady Roberts
Graham Cochran
Greg Miller
Harry Boone
Jacquelyn Deeds
James Christiansen
James Dyer
James Lindner
Jamie Cano
Jason Peake
Jim Flowers
John Ewing
John Rayfield
John Rickets
Karen Cannon
Kirby Barrick
Kirk Edney
Kristina Rickets
Lauri Baker
Leslie Edgar
Mark Balschweid
Mark Kistler
Mark Zidon
Matt Raven
April 20-23, 2011
2011 Western AAAE Research Paper Reviewers, Continued
Matt Spindler
Michael Retallick
Nicole Stedman
Nina Crutchfield
Rene Miller
Richard Joerger
Robert Birkenholz
Robert Martin
Robert Strong
Ryan Anderson
Scott Scheer
Steve Harbstreit
Susan Camp
Susie Whittington
Thomas Broyles
Todd Brashears
Tracy Rutherford
Wade Miller
Wendy Warner
April 20-23, 2011
Western AAAE Research Conference History
Year
1982
1983
1984
Location
Austin, TX
Rio Rico, AZ
Oklahoma City, OK
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
Boise, ID
Las Cruces, NM
Logan, UT
Ft. Collins, CO
Sparks, NV
Fresno, CA
Seattle, WA
Cody, WY
Bozeman, MT
Honolulu, HI
1995
1996
1997
1998
1999
Phoenix, AZ
Moscow, ID
Stillwater, OK
Salt Lake City, UT
Corpus Christi, TX
2000
Las Cruces, NM
2001
Carmel, CA
2002
2003
Spokane, WA
Portland, OR
2004
Honolulu, HI
2005
Prescott, AZ
2006
2007
2008
Boise, ID
Cody, WY
Park City, UT
2009
2010
Lake Tahoe, NV
Great Falls, MT
2011
Fresno, CA
Chair(s)
Gary E. Briers
Phillip A. Zubrick
David Cox
James P. Key
John W. Slocombe
Paul R. Vaughn
Gilbert Long
Ramsey Groves
Joseph G. Harper
James G. Leising
Marvin D. Kleene
Carl L. Reynolds
Van Shelhamer
David E. Cox
Frank C. Walton
Glen M. Miller
Jim Connors
James White
Gary S. Straquadine
Lance Keith
Jacqui Lockaby
Brenda Seevers
Robert M. Torres
William Kellogg
J. Scott Vernon
Michael K. Swan
Gregory W. Thompson
Brian K. Warnick
Martin J. Frick
Michael K. Swan
Billye B. Foster
Edward A. Franklin
Lori L. Moore
Carl L. Reynolds
Rudy S. Tarpley
Brian K. Warnick
Vernon Luft
Shannon K. Arnold
Carl G. Igo
Mollie Aschenbrener
Ann Delay
April 20-23, 2011
University
Texas A&M University
Cameron University
Oklahoma State University
University of Idaho
New Mexico State University
Utah State University
Colorado State University
University of Nevada, Reno
University of California, Davis
Washington State University
University of Wyoming
Montana State University
University of Hawaii
University of Idaho
Texas Tech University
Cal Poly, SLO
Cal Poly, SLO
Oregon State University
Oregon State University
University of Idaho
University of Wyoming
University of Nevada, Reno
CSU, Chico
Cal Poly, SLO
Table of Contents
Concurrent Research Session: A
Sheyenne Krysher, J. Shane
Robinson
Title: Teacher Education I
Discussant: Shannon Arnold
Time Keeper: Marshall Baker
Exploring the Teaching Ability Views of Agricultural
Education Student Teachers
Ashley A. Reeves, Kattlyn J. Wolf
A Descriptive Study of the Characteristics of Forestry
Education in the Pacific Northwest
Abigail C. McCulloch, Scott Burris
Is Our Recipe Working? A Study of Current Teachers'
Perceptions on the Needed Ingredients for Adequate
Teacher Preparation
Concurrent Research Session: B
Title: Extension Education
Discussant: Cindy Akers
Time Keeper: Nick Brown
Ethnography Study to Evaluate the Effects of
Community Markets for Conservation in the Central
Luangwa Valley in te Mfuwe District of Zambia
Out in the Cold About COOL: An Analysis of U.S.
Consumers' Awareness of Mandatory Country-of-Origin
Labels for Beef
Diffusion of the Animal Health Network: Understanding
Perceived Characteristics that Can Impact Adoption
Caleb Dodd, Wyatt DeJong, Brad
Leger, Scott Burris
Katie L. Allen, Courtney Meyers,
Todd Brashears, Scott Burris
Lori L. Moore, Theresa Pesi
Murphrey, Shannon H. Dagenhart,
T. Andy Vestal, Shavhan Loux
Concurrent Research Session: C
Billy McKim, P. Ryan Saucier
Edward Franklin
Ryan Saucier, Billy R. McKim
Title: Agricultural Mechanics
Discussant: Ben Swan
Time Keeper: Kevin Hartfield
A Multi-State Factor-Analytic and Psychometric MetaAnalysis of Agricultural Mechanics Laboratory
Management Competencies
Description of Agricultural Mechanics Preparation
Experience of Arizona Agricultural Education Teachers
Essential Agricultural Mechanics Skill Areas for EarlyCareer Missouri Agricultural Educators: A Delphi
Approach
April 20-23, 2011
Concurrent Research Session: D
James Haynes, J. Shane Robinson,
M. Craig Edwards, James P. Key
Allison J. L. Touchstone, Lou
Riesenberg, Russell A. Joki
Title: Teacher Education II
Discussant: Becki Lawver
Time Keeper: Karen Cannon
Determining the Effect of a Science-Enhanced Taught in
an Animal Science or Horticulture Course on Student
Science Achievement: A Causal Comparative Study
Perceived Factors Influencing High School Student
Participation in an Integrated Statewide Dual Credit
Program: An Examination of Program Success within a
College of Agricultural and Life Sciences
P. Ryan Saucier, Rob Terry, Jr.
Technical Curriculum Professional Development Needs
of Missouri School-Based Agriculture Teachers Based
Upon Career Stage
Concurrent Research Session: E
Title: Youth and Extension Education
Discussant: Kattlyn Wolf
Time Keeper: Kristin Stair
Aligning Extension Education Curriculum at Land Grant
Universities with Professional Competencies: A Delphi
Study
An Exploration of College of Agriculture Ambassador
Programs
Michelle Passmore, Shannon
Arnold, Carl Igo
Shannon Arnold
Eric W. Larsen, Carl G. Igo,
Shannon K. Arnold, Cody Stone
Youth-Adult Partnerships
Concurrent Research Session: F
Title: Teaching Effectiveness
Discussant: Theresa Murphrey
Time Keeper: Phillip Witt
Identifying Specific Items for Non-Traditional Education
Programs
Caleb Dodd, Scott Burris, Steve
Fraze, David Doerfert, Abigail
McCulloch
Caleb Dodd, Scott Burris, Steve
Fraze, David Doerfert, Abigail
McCulloch
Jonathan J. Velez, Jamie Cano
Evaluating the Effectiveness of Traditional Training
Methods in Non-Traditional Training Programs for
Adult Learners
A Descriptive Analysis of the Relationships between
Student Autonomy, Instructor Verbal and Nonverbal
Immediacy, and Classroom, Instructor, and Student
Variables
April 20-23, 2011
Concurrent Research Session: G
Mica Graybill, Courtney Meyers,
David Doerfert, Erica Irlbeck
Theresa Pesi Murphrey, Tracy
Rutherford, David Doerfert, Leslie
D. Edgar
Ashley Palmer, Erica Irlbeck,
Courtney Meyers, Todd Chambers
Concurrent Research Session: H
Kattlyn Wolf
Title: Agricultural Communication I
Discussant: Greg Thompson
Time Keeper: Martin Frick
The Use of Facebook as a Communication Tool in
Agricultural-Related Social Movements
Technology Acceptance Related to Second LifeTM,
Social Networking, TwitterTM, and Content
Management Systems: Are Agricultural Students Ready,
Willing, and Able?
A Case Study of the Risk and Crisis Communications
Used in the 2008 Salmonella Outbreak
Title: Pre-Service Teaching/Job Satisfaction
Discussant: Lori Moore
Time Keeper: Lynn Martindale
Changes in Pre-Service Teachers Agricultural Education
Teacher Self-Efficacy
Rudy Ritz
An Investigation of Pre-Service Agriscience teacher
Stress Levels, Gender, and School Size
Tracy Kitchel, Amy Smith, Anna
Ball, Shane Robinson, Rebecca
Lawver, Travis Park, Ashley Schell
Social Comparison Theory as a Lens to View Job
Satisfaction and Burnout
Concurrent Research Session: I
Title: Agricultural Communication II
Discussant: Mollie Aschenbrener
Time Keeper: Corey Ann Duysen
The Attitudes and Opinions of Agricultural Producers
Toward Sustainable Agriculture on the High Plains of
Texas
Using the Health Beliefs Model to Comparatively
Examine the Welding Safety Beliefs of Postsecondary
Agriculture Education Students and their Nonagricultural Education
Agricultural Education Pre-service Teachers' Abilities to
Teach Agricultural Mechanics
Caitlin Frederick, Courtney Meyers,
David Doerfert, Jon Ulmer
Shawn M. Anderson, Jonathan J.
Velez, Ryan G. Anderson
Brian L. Leiby, J. Shane Robinson,
James P. Key, James G. Leising
April 20-23, 2011
A Case Study of the Risk and Crisis Communications Used in the
2008 Salmonella Outbreak
Ashley Palmer, Erica Irlbeck, Courtney Meyers, Todd Chambers
Abstract
The Salmonella outbreak of 2008 was one of the largest foodborne illness outbreaks in the last
20 years. Tomatoes were initially pinpointed as the source of the outbreak, and the tomato
industry suffered losses of $100 million in 2008. Eventually, the FDA was able to trace the
outbreak to imported jalapeño peppers, but this discovery was too late to recover losses for the
tomato industry. The purpose of this study was to examine the risk and crisis communication
efforts taken by public relations practitioners in the produce industry during the 2008
Salmonella outbreak to determine which efforts were successful and which were ineffective. This
qualitative case study used the interviews of nine public relations practitioners in the tomato
industry to collect the information needed to fully explore the research objectives of the study.
The study found that all of the public relations practitioners attempted to communicate
effectively with their audiences despite the negative nature of the 2008 Salmonella crisis.
Additionally, the practitioners revealed their thoughts and perceptions about the outbreak, the
media, and the communications used during the outbreak, which provided valuable insight into
the communication efforts of an organization during a crisis.
Introduction and Theoretical Framework
The 2008 Salmonella outbreak was the largest of its kind in the past 20 years. The Salmonella
Saintpaul strain sickened more than 1,400 people in 43 states between April 16 and August 11,
2008 (Centers for Disease Control and Prevention [CDC], 2008). While the outbreak was
originally linked to certain types of raw tomatoes, it was later determined that the outbreak was
caused by imported jalapeño and Serrano peppers from Mexico tainted by contaminated
irrigation water (CDC, 2008). According to the CDC website, at least 40,000 cases of Salmonella
are reported annually, but the actual number of cases may be up to 30 times greater than those
reported, with an estimated 400 deaths a year caused by Salmonella.
Consumers are more concerned about the safety of their food than ever before, especially with
the increase in news stories about contamination and foodborne illness outbreaks (Tucker,
Whaley, & Sharp, 2006). The 2008 Salmonella outbreak heightened consumer fears about fresh
produce and caused consumers to avoid tomatoes (Bensen, 2008). These actions led to the loss of
millions in the tomato industry, despite industry-wide efforts to calm consumer fears. However,
research found many consumers were confused about the FDA’s messages as the warnings
instructed consumers to avoid certain types of tomatoes, but consumers ultimately avoided
tomatoes altogether, costing the tomato industry millions (Cuite, Schefske, Randolf, Hooker,
Nucci, & Hallman, 2009).
According to Thompson (2008), losses to the tomato industry from the impact of the 2008
Salmonella outbreak were estimated at $100 million. While the CDC maintains that tomatoes
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may have been an initial source in the outbreak, evidence of contamination in tomatoes was
never found (Thompson, 2008). Reggie Brown, vice president of the Florida Tomato Growers
Exchange, said he felt the blame on tomatoes would have been lifted sooner had the FDA
utilized tomato growers, shippers, and packers to collect information (Thompson, 2008).
Taylor, Kastner, and Renter (2009) reported that consumer fears about tainted tomatoes and the
confusion concerning FDA messages about tomatoes led to the loss of thousands of acres of fruit
in Florida just as they were about to be harvested. Many tomato farmers were unable to sell or
harvest their tomatoes due to lack of demand. While California and Georgia farmers were also
hit hard, they had already harvested their tomatoes and did not have thousands of tomatoes still
in the field as Florida farmers did (Blake, 2008). In addition to the financial loss, farmers were
also concerned that consumers had lost confidence in the tomato industry and tomato farmers
alike (Blake, 2008). The length of the outbreak and the lack of being able to pinpoint the source
of the outbreak hurt the tomato industry, as consumers stopped purchasing tomatoes during the
outbreak and were slow to return to purchasing them after the warning on tomatoes was lifted
(Taylor et al., 2009).
Risk and Crisis Communications
The role of crisis communications is to deliver information to various audiences to recover from
a crisis, prevent a future crisis, or uphold a certain reputation (Ferrante, 2010). An organization
should always be prepared for a crisis, even if they have never had to face one. Tench and
Yeomans (2006) identified three crucial steps in crisis preparation: conducting a crisis audit,
preparing a crisis management plan or manual, and practicing crisis training.
In doing a crisis audit, an organization determines its strengths, weaknesses, and vulnerabilities
while also identifying key stakeholders, a potential crisis management team, and potential crisis
situations (Heath & Coombs, 2006). According to Tench and Yeomans (2006), a crisis manual or
crisis communication plan will include contacts for key stakeholders, media contacts, key
audience messages, crisis team members and responsibilities, and brief lists of tasks to be
performed in the face of a crisis (Henry, 2000).
Ferrante (2010) listed seven steps for developing effective and appropriate risk and crisis
methods: involve the public; plan and evaluate efforts; listen to public concerns; be honest and
open; collaborate with other credible sources; meet media needs; and speak clearly and with
compassion. Additionally, an audience must feel that the organization cares, especially if death
or destruction is involved.
Risk and crisis communication plans are especially important for practitioners working for
organizations involved in the health and safety of their audience (Motta & Palenchar, n.d.).
During a crisis, a public relations practitioner’s primary responsibility is media relations in which
multiple communications must be upheld, especially an organization’s relationship with
stakeholders (Coombs, 2007).
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Ulmer, Sellnow, and Seeger (2007) proposed 10 lessons to communicate during unintentional
crises—events that create a great degree of uncertainty amongst stakeholders as well as the
public. Foodborne illness outbreaks fall into this category.
 Accept that a crisis is unexpected and can occur rapidly
 The response of an organization to a crisis should be unique to the crisis at hand
 The threat of a crisis is perceptual
 Communicate immediately and often throughout the crisis, even if the organization
does not have critical information
 Do not withhold or alter any information to the public in an attempt to be ambiguous
 Prepare to defend evidence or facts presented during the crisis
 Operate with good intentions, otherwise recovery from the crisis is nearly impossible
 Believe that the crisis responsibility relies with the company. A case should be
presented as to who should take the crisis responsibility and why
 Examine business practices during and after the crisis
A crisis communication plan enables an organization to be proactive which, in turn, puts the
organization in a position to be in control when a crisis strikes, as an organization moves along in
a crisis situation, the plan should allow it to adapt to any and all changes while also protecting
itself (Leighton & Shelton, 2008).
Excellence Theory
This study was guided by the concepts put forth by two-way symmetrical communications, or
the excellence theory (Grunig & Hunt, 1984). According to Grunig, Grunig, and Dozier (2002),
public relations is a function of management that describes how organizations and stakeholders
interact with one another during the decision making process. Grunig (1992) explained that the
effectiveness of an organization is determined in part by the organization’s ability to identify key
stakeholders and develop and maintain a mutually beneficial relationship with said stakeholders.
An organization’s stakeholders can affect the organization’s ability to achieve its goals and in
turn, an organization can have the same affect on stakeholder goals (L. Grunig et al., 2002).
Symmetrical communications between an organization and its stakeholders is key when
developing organization relationships (L. Grunig et al., 2002). Symmetrical communication is a
two-way process that ―p
ractices equal communication between the organization and the
audiences‖ (Baldwin, Moffitt, & Perry, 2004, p. 319) where an organization is willing to alter its
practices based upon audience research to benefit both the organization and its audiences.
Purpose and Objectives
The purpose of this study was to examine the risk and crisis communication efforts taken by
public relations practitioners in the produce industry during the 2008 Salmonella outbreak and
determine which efforts were successful and which were not.
The following research objectives were used to guide this case study:
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1. Determine public relations practitioners’ opinions of the effectiveness of their
organization’s communication efforts during the 2008 Salmonella outbreak.
2. Explore the lessons public relations practitioners’ learned as a result of their involvement
in the 2008 Salmonella outbreak.
3. Describe public relations practitioners’ perceptions of mass media coverage during the
2008 Salmonella outbreak.
4. Understand risk and crisis communication actions taken by companies impacted by the
This study fits under the National Research Agenda, Research Priority Area 1 in Agricultural
Communications: Enhance Decision Making Within the Agricultural Sectors of Society
(American Association for Agricultural Education, 2007). This priority area seeks to analyze the
effectiveness of communication efforts and determine the most effective way to communicate
and disseminate information about high priority agricultural issues.
Method
This research employed case study methodology ―
to gain an in-depth understanding of the
situation and meaning for those involved,‖ (Merriam, 1998, p. 19). Yin (2003) explained that
qualitative data cannot be described through numerical data, but should be described by events,
perceptions, attitudes, and categorical data. Miles and Huberman (1994) found that in defining a
case study, a researcher must have clearly defined boundaries that state what will and will not be
studied.
The case for this study was the 2008 Salmonella outbreak and the public relations practitioners
who were directly involved with communication efforts during the outbreak on behalf of a
company or organization in the tomato industry. Practitioners who were not involved in
communication efforts related to the tomato industry during the 2008 outbreak or companies not
directly impacted by the outbreak were excluded from this study, as were other foodborne illness
crises.
Subjects were located through the Google search tool and various databases available through
the university library, using these search terms: 2008 Salmonella outbreak, tomato growers,
tomato associations, produce associations, and tomato group. Potential interview participants
were contacted by e-mail or telephone to build rapport, provide study information, and request a
telephone interview. Subjects who agreed to do the interview were then sent a consent form by email. In all, nine public relations practitioners or company executives that served as the public
relations officer during the 2008 outbreak were interviewed for this study. In addition, the
researchers asked each participant if they would suggest anyone else to interview for the study.
After five interviews, the participants were naming the same people; therefore, the researchers
were confident that most of the public relations practitioners in the tomato industry were
reached.
This study utilized a semi-standardized interview (Berg, 2009), where the interview questions
were composed ahead of time based upon the research objectives of the study. During the
interviews, the researcher asked additional, non-scripted questions where probing was needed to
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better suit the interviewee. The interview guide was categorized by demographic questions, 2008
Salmonella outbreak questions, media questions, and risk and crisis communication questions.
Telephone interviews are more practical, allow greater uniformity in interview delivery, and
allow researchers to contact individuals in other areas when travel to the interviewee is not
possible (Charmaz, 2003). The interviews for this study were conducted by telephone because
travel was not funded for this study, nor would time allow for travel to the various locations of
interviewees across the United States.
Interviews averaged 30 minutes in length, and all were recorded. The researcher transcribed each
interview as soon as possible after the interview, and in keeping with the confidentiality
guidelines proposed by Berg (2009), only one researcher transcribed data. The data were then
coded using NVivo qualitative data analysis software. Each of the nine participants were
assigned a pseudonym to protect anonymity.
To achieve trustworthiness, the researcher triangulated data with findings from previous studies
(Irlbeck, 2009) The researcher also employed member checks, addressed bias, and kept an audit
trail (Merriam, 1998; Niekerk & Savin-Baden, 2010). The researcher has a background in both
agriculture and communications, and tended to sympathize with agricultural producers. While
the researcher has no direct ties to the produce industry, the researcher has strong feelings about
the agricultural industry and its role in supplying food to the United States and other countries.
Findings
Nine individuals were interviewed for this study. Four worked in public relations or issues
management for trade organizations; two were food safety experts at distributions facilities; one
was a CEO of a packing, growing and distribution company; one was a public relations
practitioner at a non-profit organization; and one was the director of communications for a
grocery chain in the South.
Findings in Relation to Research Objective 1
Research objective one sought to determine public relations practitioners’ opinions of the
effectiveness of their organization’s communication efforts during the 2008 Salmonella
outbreak. Four main themes emerged from the data in relation to Objective 1: communication
goals, effective communication, ineffective communication, and organization success during the
Many of the subjects reflected their concern for both public health as well as stakeholder wellbeing in their communication goals for their message platforms used while mitigating the 2008
Salmonella outbreak. Many of the organizations emphasized the need of the organization to get
information out quickly to consumers, stakeholders, and industry counterparts, so that all
concerned would be able to make educated decisions.
MAUREEN (Director of comm. for trade org.): People do have a right to know certain
things, and as a public relations person, the best you can do in a crisis is to deliver good,
accurate, timely, correct information to the media so they will get their story right.
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Brianne touched on relationships with media, but also stated that positive relationships with
regulators and the FDA aided in her company’s ability to effectively communicate with their
audiences.
BRIANNE (Issues management at nonprofit): I think our constant engagement with the
media, the constant availability to Congress, working and having good relationships with
FDA so we got separated out quickly. So we were part of the wave, but we were able to
separate ourselves out. I think those efforts were successful, yes.
Participants were asked what communication efforts were ineffective or were not as successful
as the company or organization had hoped. Many of the subjects had similar responses to
Brianne’s— their organization did the best possible, given the enormity of the crisis.
BRIANNE (Issues management at nonprofit): In a crisis nothing ever goes as planned.
There’s nothing that I would say didn’t work, because of what we were up against, you
know we were up against this huge tide.
Overall, all of the practitioners interviewed said their company or organization handled the crisis
―
as well as conditions would permit,‖ said Orson, given the complexity and nature of the 2008
Salmonella outbreak.
Research objective two sought to explore the lessons learned by public relations practitioners as
a result of their involvement in the 2008 Salmonella outbreak. Two themes emerged: overall
lessons learned and organization changes.
An organization must be willing to communicate effectively. If not, the communication
messages of the organization will never get out, and the organization will sustain even more
damage.
SHELDON (Director of comm. for grocery chain): Don’t ever try to hide. No matter how
much you would like to, and how much you would like to say no comment that’s the worst
possible thing you can do. The best possible thing you can do is to get out and be public
with the situation and be open and honest with the communication as quickly as possible
with as much accurate information as you can provide.
BILL (Food safety VP at distribution comp.): You cannot be intimidated by the media.
You have to be on the offensive if there are issues that are pertaining to the products that
you are producing. It is your image out there, and you have to do image control.
When it comes to communicating with government agencies, Orson stated that his organization
had to focus on communications with the FDA, and provided a very simple lesson he took away
from the crisis.
ORSON (CEO of growing, packing, shipping comp.): We had to focus our efforts on the
governmental agencies because nothing we said in the public arena was going to be
accepted as factual. Be aggressively responsive to the governmental inquiries. Stick to the
facts and communicate them with every breath you have.
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Many of the interviewees also said they did not realize the impact the FDA communication
efforts would have on the tomato industry. The majority of the subjects stated that this crisis
highlighted the need for improved communications between the FDA and industry officials and
organizations in the face of a crisis.
MAUREEN (Director of comm. for trade org.): I think we felt that we were being framed
negatively by the government, by the FDA. The FDA and CDC have some ways to go
when it comes to a crisis like this.
About half of the interviewees reported that no changes were made, but that policies and
procedures were reviewed to ensure that no changes were necessary and to determine the
effectiveness of the measures taken by the organization during the 2008 crisis.
BILL (Food safety VP at distribution comp.): I don’t know that we decided to change
anything, we just decided that yep, although the mock drills are nice, in a real world
situation this does work. I think what it did was give us some piece of mind.
Research objective three sought to describe public relations practitioners’ perceptions of mass
media coverage during the 2008 Salmonella outbreak. Two themes emerged: perceptions of
media coverage and consumer interpretation of media messages.
The perceptions of practitioners about the national media coverage during the 2008 Salmonella
outbreak varied greatly. Some participants praised the quality of the media coverage, while
a feeding frenzy,‖ based upon
others, like Bill, found the coverage to be equivalent to ―
inaccurate information and facts. The participants who praised the media coverage found the
coverage to be fair even though the subject matter was negative by nature.
MAUREEN (Director of comm. for trade org.): The media played an integral role in the
investigation and in public health, they did their job. I don’t think we have any complaints
about how the media reported this story because we spoke with them.
On the other hand, some of the interviewees were very angry at the national media coverage of
the outbreak and expressed strong opinions about information they felt was falsely portrayed in
the media coverage.
TIM (director of food safety at a re-packing facility): I have to hold back on some
profanity here, I think it was just bizarre. It was just awful. Again, anybody who had any
produce experience would have know that there was no way that [those] tomatoes had
anything to do with the outbreak. It would have just been common sense.
When interview participants were asked how they thought consumers interpreted the messages
put out by the national media, the overwhelming response dealt with consumer confusion.
BRIANNE (Issues management at nonprofit): There was confusion at a lot of different
levels from FDA’s trace back and the way they communicated with consumers on the
outbreak was extremely confusing. FDA had maps, blue and red maps that showed where
outbreaks were, there are numerous varieties of tomatoes so they would list the varieties
that weren’t involved, could be involved, and the consumer just threw up their hands and
said forget it, I won’t purchase anything right now.
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Research objective four sought to understand the risk and crisis communication actions taken by
companies impacted by the 2008 Salmonella outbreak. Three themes emerged from the data:
communication actions, crisis communication plan, and advice to others.
With the onset of a crisis, organizations are required to immediately jump into a crisis in order to
mitigate damages and get their messages out. Many of the practitioners stated that they
immediately activated their crisis communication plans and teams. Maintaining communication
with all pertinent audiences and stakeholders was top priority for all of the participants and many
used a variety of methods to maintain these communications.
Of the nine public relations practitioners interviewed, only two reported not having or using a
crisis communication plan. The other seven practitioners all had a crisis communication plan for
their organization that was in place before the crisis and was used to guide each through the 2008
Salmonella outbreak.
While the components of a crisis communication plan do not have to be complicated,
participants shared their opinions on important components in their organization’s plan. As
previously stated in the findings, the crisis communication team is identified and duties assigned
in the crisis communication plan. Additionally, all of the participants collectively referenced
other common components.
Many of the practitioners indicated that an organization should be proactive in looking for signs
of risk, and should be ready to act on those risk factors.
BRIANNE (Issues management at nonprofit): I always hope for the best but we are always
prepared for the absolute worst. Putting systems in place if the worst happens so you are
ready to execute.
SUSANNE (VP of comm. at trade org.): Know where your potential weaknesses are, plan
for those weaknesses to mitigate them from happening. Create a crisis team, create a crisis
plan. Make a living document, don’t sit it on the shelf and say, oh we did that job and
move on to 87 different things.
Conclusions
When examining the responses of all of the interviewees, all participants felt that their
organization handled the 2008 Salmonella crisis in the most efficient and effective way that they
were capable of. None of the interviewees reported any large-scale mismanagement on the part
of their organization. While all of the organizations and companies represented by practitioners
in this study were negatively impacted by the crisis, none of interviewees solely faulted the
media for the losses sustained during the 2008 Salmonella outbreak. The media coverage was
acknowledged as a contributing factor, but not all of the practitioners found the media coverage
to have a negative impact on their organization.
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Ferrante (2010) stated that an organization must show concern for the public, especially when
health and safety is involved, and must protect the organization’s stakeholders in a crisis.
According to Norah, organizations in the tomato industry during the 2008 Salmonella outbreak
sought to do just that. ―
The communication goals were to number one, above everything else,
protect public health.‖
Grunig et al. (2002) stated that an organization must be able to engage in two-way symmetrical
communications with stakeholders. An organization that incorporates this communication style
and is able to maintain a beneficial relationship with stakeholders is practicing excellent
communications (Grunig & Hunt, 1984). Many of the goals discussed by the interviewees
incorporated two-way symmetrical communications in order for the organization to be effective
and successful in their efforts. The researcher concluded that all of the organizations attempted to
practice the excellence model by communicating with stakeholders, and then adjusting messages
based on stakeholder influence (Grunig and Hunt, 1984).
The organizations represented also employed two of the principles outlined by Vercic, Grunig
and Grunig (1996) in that the managers did guide the communication efforts during a crisis, and
the organizations did communicate with stakeholders in a two-way symmetrical manner.
Ferrante (2010) found that an effective crisis communication message must be clear and concise,
especially if the audience is expected to take certain actions. Many consumers became frustrated
with the mixed messages they received, and stopped purchasing and eating tomatoes, or ignored
the messages all together (Cuite et al., 2009). Based upon the findings and the literature, many
participants believed some of the messages communicated during the 2008 Salmonella outbreak
were ineffective due to a lack of clarity, which may have contributed to some of the losses
suffered by the tomato industry even though the confusing messages were not disseminated by
the tomato industry.
Ulmer et al., (2007) defined a foodborne illness outbreak as an unforeseeable, unavoidable crisis
that creates high levels of uncertainty. Due to the nature of the Salmonella outbreak, all but one
of the participants said they abided by the lessons outlined by Ulmer et al., (2007) to reduce
uncertainty in a foodborne illness outbreak.
Additionally, all of the practitioners said their organizations communicated as effectively as
possible given the nature of a crisis, which is supported by the findings of L. Grunig et al.,
(2002). While the outcomes of the 2008 Salmonella outbreak were unfavorable for the tomato
industry, these outcomes were unpredictable and were not the result of failed communication
efforts on the part of the tomato industry.
Ulmer et al., (2007) found that organizations can only be successful in a foodborne illness
outbreak if it examines its practices and communication efforts after the crisis. The majority of
the practitioners reported going over their practices and procedures after the 2008 Salmonella
outbreak, which was important in determining effective and ineffective communication efforts.
The perceptions of the participants about the national media coverage were mixed. Some said the
media coverage was extremely negative while others found the media coverage was fair to the
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April 20-23, 2011
tomato industry even though the message was negative, as evidenced by Maureen’s comment,
―
The media played an integral role in the investigation and in public health, they did their job. I
don’t think we have any complaints about how the media reported this story because we spoke
with them.‖
The researcher observed that those practitioners who said the national media coverage was fair
and accurate had positive interactions and communications with the media, whereas those
practitioners who had limited or no contact with the media generally had negative perceptions of
the media coverage. All of the participants concluded that consumer interpretation of the mass
media messages was that of mass confusion. Consumers were confused about which tomatoes
were safe to eat, and which were not, and when faced with this confusion, consumers either
stopped consuming tomatoes or completely disregarded the messages (Cuite et al., 2009). Due to
those actions taken by consumers, the tomato industry suffered losses both in and out of the field.
Tench and Yeomans (2006) described crisis management as the preparation of an organization
before a crisis, the management of the crisis, and the re-establishment of the organization after
the crisis. The subjects outlined the communication actions taken by their organizations that were
developed to meet their organization’s needs and communicate effectively. Almost all of the
subjects referenced the following communication actions:
 Information gathering
 Notification of stakeholders
 Activation of crisis communication plan and or crisis communication team
 Dissemination of messages
 Maintenance of communications with stakeholders
Each of the participants were asked what advice they would give to other public relations
practitioners who might face a similar crisis based upon experience with the 2008 outbreak. The
findings to this response as well as those of research objective two allowed the researcher to
develop a list of Do’s and Don’ts pertaining to communication during a foodborne illness
outbreaks and possibly other food related crises (see Table 1).
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April 20-23, 2011
Table 1
Do’s and Don’t’s of crisis communications during a foodborne illness outbreak
Do
Don’t
Have a crisis communication plan
Think it can’t happen
Monitor for potential risks
Ignore the warning signs
Practice two-way communications
Be ambiguous
Provide timely and accurate information
Lie or be dishonest
Collaborate with industry counterparts
Chastise government agencies
Develop and maintain governmental
relationships
Ignore key audiences or stakeholders
Conduct a crisis audit/mock drill
Hide from the media
Reach out and utilize the media
Stay silent
Keep up with important contacts
Downplay public health
Some of the proposed guidelines are applicable to crisis situations in any industry, but due to the
unique nature of a foodborne illness outbreak, the researcher believes these guidelines as a whole
are especially pertinent to the food industry. Many of the participants mentioned the unusual
nature of the 2008 Salmonella outbreak, in part because of the length of the outbreak, but also
because tomatoes were never cleared as a possible source of contamination. These findings make
it imperative for those in the food industry seek out media outlets to provide consumers with
their messages. Although it is the tendency of those in the food and agriculture industry to shy
away from media sources, getting out their messages and information will aid in reducing the
damages suffered by an industry during a foodborne illness outbreak.
For practitioners
Recommendations
Perhaps the most important recommendation that could easily be implemented into any risk and
crisis communications plan is for practitioners to develop contacts with the media. Practitioners
who had positive impressions of the media during the 2008 crisis tended to have an established
relationship with reporters.
In addition to developing contacts with the media, the researchers recommend creating better
lines of communication with governmental agencies. While this study did not probe into industry
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April 20-23, 2011
relations with the FDA and CDC, the researcher could not ignore the resentment and anger many
of the interview subjects portrayed in their interviews toward the FDA especially, regarding the
2008 Salmonella outbreak. Orson expressed his feelings concerning the FDA.
ORSON: You have the public stakeholders, which is our customers and our customer’s
customers. Then you have the governmental stakeholders. Well the public stakeholders and
the and the media that provides information to them, or the mediums, only listen to the
government, and the government was providing inaccurate, untimely, information. So we
had to focus our efforts on the governmental agencies because nothing we said in the
public arena was going to be accepted as factual.
This research study found that practitioners were also frustrated with the confusion surrounding
the messages put out by the FDA. Irlbeck (2009) found that the FDA lost some credibility due to
its communication efforts and the length of time it took them find the true source of the
contamination during the 2008 outbreak. A study conducted by the Rutger’s Food Policy
Institute found that consumers were confused by the FDA’s messages, and the confusion led to
additional losses in the tomato industry (Cuite et al., 2009).
The food and agriculture industries tend to shy away from the media, and often the media is
forced to look outside of the industry for interviews and information (Eyck, 2000). If
practitioners are able to improve communication efforts with governmental agencies, it could aid
both parties in disseminating united messages to consumers and could also aid investigative
efforts in future possible crises. In doing this, produce industry officials would hopefully be able
to prevent some of the unnecessary losses sustained by the tomato industry during the 2008
Salmonella crisis.
Based upon previous literature and the findings from this study, the researcher suggests using the
guidelines presented in this case study to guide practitioners in planning for a future crisis. Given
the information garnered from the literature review and the suggestions of the participants, the
researcher suggests following these steps in developing a plan:
1. Identify a crisis communication team and duties of each member of the team should the
organization become involved in a crisis (Ulmer et al., 2007).
2. List all stakeholders and audiences that the organization communicates with
3. Gather contact information for stakeholders, board of directors, media sources, and any
other contacts that may be a valuable resource during a crisis (Ferrante, 2010).
4. Develop key messages to disseminate to stakeholders and goals of the communication
efforts to be used. Also determine how these messages will be dispersed.
5. Identify trustworthy media sources to be contacted at the beginning of a crisis to tell the
organization’s side (Coombs, 2007).
6. Conduct a crisis audit or mock drill at least once a year to test all of the materials and
methods and to check for possible updates.
7. Be on the offensive, be monitoring for a crisis and be ready to respond at the beginning of
a crisis with timely and accurate information to all stakeholders, including the media.
Based upon the findings of this study, these steps, and the provided guidelines are important to
communicate effectively with all stakeholders and may aid an organization in mitigating the
damages suffered during a crisis, such as profit losses.
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April 20-23, 2011
For Future Research
This case study researched the risk and crisis communications taken by public relations
practitioners during the 2008 Salmonella crisis. To gain a more thorough understanding of the
depth of the damages sustained by the tomato industry during the 2008 Salmonella outbreak, a
study is needed to determine the long term impacts the 2008 outbreak had on the tomato
industry. A study of this nature would possibly provide information that would aid in the creation
of a model for practitioners to use during a food related crisis that took into account long-term
effects on an industry.
To further understand the risk and crisis communications utilized during a crisis, further research
needs to be conducted pertaining to other food related crises in order to generalize these findings
beyond this study. Additional research would be especially pertinent to this issue when
examining more recent cases of foodborne illness outbreaks, such as the 2010 Salmonella
outbreak in eggs or the 2009 peanut butter recall, also due to Salmonella.
13
April 20-23, 2011
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A Descriptive Analysis of the Relationships between Student Autonomy, Instructor Verbal
and Nonverbal Immediacy, and Classroom, Instructor, and Student Variables
Jonathan J. Velez, Oregon State University
Jamie Cano, Ohio State University
Abstract
This study sought to descriptively explore verbal immediacy, nonverbal immediacy and student
autonomy in relation to classroom, instructor and student variables. Respondents (N = 208)
assessed the verbal and nonverbal immediacy of their instructors and their autonomy in a
particular course. Regarding classroom variables, students enrolled in elective courses rated
their instructors as higher in verbal immediacy, nonverbal immediacy, and autonomy-supportive
behaviors. Verbal immediacy was rated highest for class sizes of 0-29 and decreased as class
sizes increased. The verbal immediacy effect size difference between class sizes of 0-29 and 150
or more was strong at d = 1.46. In terms of instructor variables, instructors increased in verbal,
nonverbal and autonomy-supportive behaviors through the age categories, peaking at 50-59
years of age. Female instructors scored higher in all three categories than their male
counterparts. The student variables indicated that perceptions of verbal immediacy and
autonomy-supportive behaviors increased with student age; while nonverbal immediacy
remained consistent. Relationships between verbal immediacy, nonverbal immediacy, and
autonomy were positive, moderate to very high relationships (r = .538, .601, and .819).
Rationale for the differences were analyzed in light of both theoretical and practical application
and recommendations for future research are provided.
Introduction
In 1997, the American Psychological Association revised what was, in 1990, the
groundbreaking concept of learner-centered instruction. The educational world was once again
clearly presented with the importance of considering student involvement in the learning process.
The APA called for an increased focus on student attributes, and awareness of motivational
tendencies, and an understanding of ways to enhance the learning environment (American
Psychological Association, 1997). Research has indicated that one of the ways to enhance
student motivation is by offering choices and allowing students to develop a sense of autonomy
(Deci, Vallerand, Pelletier, & Ryan 1991; Deci & Ryan, 2002). The APA task force (1997)
supported offering choices and stated, “Educators can encourage and support learners' natural
curiosity and motivation to learn by attending to individual differences in learners' perceptions of
optimal novelty and difficulty, relevance, and personal choice and control” (p. 5). Based on
recommendations to encourage and support personal choice and control within the learning
environment, recent attention has shifted to the construct of student autonomy, embedded within
the Theory of Self-Determination (Deci & Ryan, 2002; Deci & Ryan, 2007).
Given the importance of student motivation and based on the need to provide autonomy,
the present research sought to examine student motivation through the analysis of student
autonomy and a corresponding analysis of teacher traits. However, more specifically, the
researchers sought to explore motivation within the context of agriculture. The National
April 20-23, 2011
Research Agenda (Osborne, 2007) called for research with the potential to, “improve the success
of students enrolled in agricultural and life sciences academic and technical programs” (p. 7).
Furthermore, the National Research Agenda also called for research which had the capacity to
improve the effectiveness of faculty in shaping and guiding the teaching and learning process
(Osborne, 2007).
This research originated out of the need to begin exploring the autonomy motivation of
students enrolled in agriculture and corresponding student perceptions of instructor behaviors.
According to Wentzel and Wigfield (1998), “Researchers need to explore further how different
classroom and interpersonal contexts influence students’ academic and social motivation” (p.
170). Developing an understanding of student motivation is a foundational area for improving
student success for students enrolled in agriculture. Hofer (2006) stated that, “Knowing more
about how students are motivated and what you can do to structure a class that positively affects
student motivation can make a significant difference in student engagement and learning”(pp.
140-141).
Theoretical Foundation
The theoretical foundation for this research was grounded in two main theories, SelfDetermination Theory and the Implicit Communication Theory. Both theories are intricately
connected to the social and contextual aspects of learning.
Self-Determination Theory (SDT) is a macro-theory of human motivation dealing
primarily with the development of personality within social contexts (Deci & Ryan, 2007). Deci
and Ryan (2007) describe SDT as a theory which, “. . . focuses on the degree to which human
behaviors are volitional or self-determined -- that is, the degree to which people endorse their
actions at the highest level of reflection and engage in the actions with a full sense of self choice”
(p. 1). Self-determination, as a theory, focuses on the experience of choice with an emphasis on
an internally perceived locus of control. Deci and Ryan (1985) stated that, “. . . selfdetermination is the capacity to choose and to have those choices, rather than reinforcement
contingencies, drives, or any other forces or pressures, be the determinants of one’s actions” (p.
38). Self-determination theory focuses on an individual’s autonomy and perceived freedom in
relation to a given social or situational context.
Self-Determination Theory consists of four mini-theories; Cognitive Evaluation
Theory, Organismic Integration Theory, Causality Orientations Theory, and Basic Needs
Theory (Deci & Ryan, 2002). Of the four mini-theories, Cognitive Evaluation Theory
(CET) forms the direct theoretical basis for student autonomy. Deci and Ryan (2002)
state that CET is, “formulated to describe the effects of social contexts on people’s
intrinsic motivation” (p. 9). Specifically the CET delineates autonomy-supportive,
controlling and amotivating environments. The Cognitive Evaluation Theory, at its
inception, was intended to account for reward effects on intrinsic motivation. Simply
stated, contextual events have the opportunity to either negatively or positively affect
intrinsic motivation. Deci and Ryan (2002, 2007) suggest perceived locus of causality
and perceived competence as two primary cognitive processes through which contextual
factors influence intrinsic motivation.
April 20-23, 2011
The CET combines both perceived locus of causality (autonomy) and perceived
competence in relation to intrinsic motivation. Deci and Ryan (2002) stated that, “According to
CET, however, positive feedback is predicted to enhance intrinsic motivation only when people
feel a sense of autonomy with respect to the activity for which they perceived themselves to be
competent. . .” (p.11). The influential role of autonomy in the enhancement of intrinsic
motivation is of paramount importance to the Cognitive Evaluation Theory.
In summary, the contextual and atmospheric conditions of an event, whether controlling
or informational, have the ability to direct an individual’s motivation in either an intrinsic or
extrinsic direction. Deci and Ryan (2002) stated that, “. . . CET holds that self-controlling
forms of regulation will be associated with diminished intrinsic motivation, whereas more
autonomous forms of self-regulation will maintain or enhance intrinsic motivation” (p. 13). An
informational (autonomy supporting) atmosphere has the ability to shift towards an internal
perceived locus of causality, and thus increase intrinsic motivation (Deci & Ryan, 2002).
In 1969, Albert Mehrabian developed a communication theory to describe the often
subtle aspects of communication. He termed his theory the Implicit Communication Theory
(ICT) and referred to it as “our theory.” While the present researchers were in no way influential
in the establishment of the Implicit Communication Theory, the verbiage used implies a sense of
cohesion, unity and belonging. The word choice employed by Mehrabian is specific and
intentional, designed to induce within the reader feelings of personal involvement, closeness, and
belonging (Mehrabian, 1969, 1981).
The ICT was grounded in the concept that messages are constantly transmitted via a
measure of verbal and non-verbal communication referred to as immediacy. Mehrabian
postulated that, “. . . people rarely transmit implicitly the kinds of complex information that they
can convey with words; rather, implicit communication deals primarily with the transmission of
information about feelings and like-dislike or attitudes. . .” (Mehrabian, 1981, p. 3). Mehrabian
based his theory on five major categories of implicit behaviors (Mehrabian, 1981). The five
major categories include: emblem (e.g. handshake, smile, nod), illustrator (e.g. pointing gestures,
hand and head movements used to stress primary words), affect display (e. g. happiness, fear,
anger, surprise), regulator (e.g. indicators to keep talking, clarify, hurry up), and adaptor (e.g.
changing positions, scratching, shifting weight ) (Mehrabian, 1981).
Based on the five categories, Mehrabian developed the concept of verbal and nonverbal
immediacy. Immediacy has been defined as those communication behaviors which, “ . . .
enhance closeness to and nonverbal interaction with another” (Mehrabian, 1969, p. 203).
Verbally immediate behaviors refer to the stylistic expressions used by teachers to develop
feelings of closeness within the students. Examples include probability statements (will vs.
may), inclusive references (we vs. I), ownership statements (my/ our class), and syntactic
expressions of present or past tense verbs (Rubin, Palmgreen, & Sypher, 1994). Nonverbal
immediacy has been defined as the implicit use of closeness-inducing behavioral cues and has
largely been perceived to convey affective feelings of warmth, closeness, and belonging
(Richmond, Gorham, & McCroskey, 1987). In 1979, Andersen studied the effects of nonverbal
April 20-23, 2011
immediacy on affective learning and concluded that, “The more immediate a person is, the more
likely he/she is to communicate at a close distance, smile, engage in eye contact, use direct body
orientation, use overall body movement and gestures, touch others, relax, and be vocally
expressive” (p. 548).
Conceptual Framework
Self-Determination Theory, and the concept of autonomy, share a strong conceptual
relationship with student motivation. Instructors who provide students with autonomy, facilitate
intrinsic student motivation (Deci & Ryan, 2002). Autonomy-supportive behaviors are teacher
behaviors which allow students the opportunity to develop an internal locus of control, thus
enhancing intrinsic motivation. In describing the relationship between external and internal locus
of control, Deci and Ryan (2002) stated that, “when an event prompts a change in perceptions
towards a more external locus, intrinsic motivation is undermined; whereas, when an event
prompts a change toward a more internal perceived locus, intrinsic motivation will be enhanced”
(p. 11). When teachers provide students with autonomy, and students make self-directed
choices, student intrinsic motivation will increase (Deci & Ryan, 2002). Autonomy also serves to
enhance student perceived competence. When an event increases perceived competence in an
area, the individual is more likely to be intrinsically motivated by a task; whereas, when an event
undermines perceived competence, the individual is likely to evidence diminished intrinsic
motivation (Deci & Ryan, 2007).
It is important to understand the terminology associated with autonomy. Classroom
climate (in this study measured by the Williams and Deci Learning Climate Questionnaire
(1996)) is a measure of how the students feel in a given classroom. The students are asked to
assess feelings such as, how they feel about an instructor, the choices or options they are
provided, and whether they feel cared for or understood by the instructor.
Verbal immediacy has been studied in communication research since the late 1970s and
the results indicated there are several benefits to a verbally immediate environment. Verbal
immediacy has been linked in the literature with effective teaching (Gorham, 1988) and has
shown relationships with affective learning, student motivation, and perceived cognition
(Christophel, 1990). Research indicates that students engaged in a verbally immediate
environment show an increased willingness to participate and contribute to class discussions
(Christensen, Curley, Marquez, & Menzel, 1995; Menzel & Carrell, 1999). According to
Christophel (1990), Gorham (1988), and others, verbal immediacy appears to increase student
cognitive, affective, and behavioral learning (Gorham & Christophel, 1990; Plax, Kearney,
McCroskey, & Richmond, 1987).
Related specifically to teaching, past researchers have discovered that immediate
instructors foster increased student liking, decreased student apprehension and increased liking
for the subject and course (Butland & Beebe, 1992; Rodriguez, Plax, & Kearney, 1996; Plax,
Kearney, McCroskey, & Richmond, 1987). Common verbal immediacy teaching expressions
include humor, self-disclosure, praising student efforts, engaging students in conversations,
willingness to meet with students and overall openness (Edwards & Edwards, 2001; Gorham,
1988).
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According to Richmond, Gorham, and McCroskey (1987), nonverbal immediacy is a
relational language perceived to convey affective feelings of warmth, closeness, and belonging.
Nonverbal immediacy is conceptualized as behaviors which are perceived to promote feelings of
arousal, pleasure, liking and dominance. These behaviors are expressed through actions such as
personal touch, body movement, physical proximity, and eye contact (Richmond, Gorham, &
McCroskey 1987). Research indicates that nonverbal immediacy has been associated with
student motivation, trait and state motivation, and has explained a significant portion of the
variance in attitude towards instructor and tendency to enroll again (Christophel, 1990; Gorham
& Christophel, 1992; Frymier, 1994; Christophel & Gorham, 1995).
Most of the preceding literature review contains a notable absence of agricultural
education citations because, in agricultural education, there has been little published research
pertaining to immediacy and student motivation. Velez and Cano (2008) examined the
relationships between verbal immediacy, nonverbal immediacy and student motivation. The
results showed a relationship between nonverbal immediacy and expectancy-value motivation as
well as a difference in immediacy between graduate students and professors (Velez & Cano,
2008). Murphrey, Arnold, Foster & Degenhart (2010) examined verbal immediacy in relation to
audio technologies and concluded that there was a significant difference between graduate and
undergraduate students in relation to feedback and verbal immediacy in an online course. A few
agricultural education authors have alluded to self-determination and the construct of student
autonomy ( Knobloch, 2006; Linder, Dooley, Kelsey, 2002;) yet a review of the literature was
unable to uncover studies with a substantial emphasis on student autonomy.
While there has been very little research done within agricultural education, the fields of
education and communication have highlighted the theoretical and practical similarities between
immediacy and student autonomy. Immediacy is very much contextually driven, as is student
autonomy. Immediacy tends to measure low inference (specific behaviors) while autonomy
assesses the overall classroom climate. Both are highly influenced by the instructor, and both
contain theoretical and practical implications for student motivation (Deci & Ryan, 2002).
Purpose and Research Questions
The study sought to describe the verbal and nonverbal immediacy of instructors and
determine the relationships between immediacy and student perceptions of autonomy. The
research was guided by four main research objectives.
Obj. 1: Describe instructor levels of verbal and nonverbal immediacy, and corresponding student
perceptions of autonomy, based on classroom variables.
perceptions of autonomy, based on instructor variables.
perceptions of autonomy, based on student variables.
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Obj. 4: Examine the relationships between instructor verbal and nonverbal immediacy and
student perceptions of autonomy.
Research Methods
The target population for this descriptive-exploratory study consisted of college students
enrolled in two selected agricultural courses within [state] university. A purposive sample was
selected and assessed from two of the largest non-major specific agriculture courses offered by
the college. According to Ary, Jacobs, Razavieh and Sorensen (2006), a purposive sample is one
in which, “. . . sample elements judged to be typical, or representative, are chosen from the
population” (p. 174). The two courses in which the assessment was administered were identified
and selected based on class size, accessibility, and enrollment of a diverse variety of majors.
Data were collected from the two selected courses in which students were asked to assess
their personal motivation in the class they had attended immediately previous to the class in
which collection occurred. The method of collection, commonly used in past research studies
(Plax, Kearney, McCrosky, & Richmond, 1987; Gorham, 1988; McCroskey, Richmond, &
Bennett, 2006; Gorham & Christophel, 1992), was intended to maximize variability and
minimize threats to validity. Both classes were deemed to be courses which were most closely
representative of the entire college. However, based on the nonprobability method of collection,
no attempt was made to generalize the results beyond the respondents (Ary et al. 2006). While
the data utilized in this study were part of a larger study, the current research focused strictly on
the classroom, instructor and student variables relating to student autonomy and verbal and
nonverbal immediacy.
The researchers utilized three different instruments, including demographic questions, to
collect data pertaining to the objectives. The Nonverbal Immediacy Behaviors (NIB) instrument
consisted of 14 Likert type questions, each ranging from 1 (Never) to 5 (Very Often). In previous
studies, the Nonverbal Immediacy Behaviors instrument has demonstrated summated reliabilities
ranging from 0.73 to 0.89 (Christophel, 1990; Richmond et al., 1987). The pilot study (n = 27)
revealed a Cronbach’s reliability coefficient of 0.82.
The Verbal Immediacy Behaviors (VIB) instrument consisted of 20 Likert type questions,
each ranging from 1 (Never) to 5 (Very Often). The Verbal Immediacy Behaviors instrument had
previously attained alpha and split-half reliabilities ranging from .83 to .94 (Christophel, 1990).
The pilot study (n = 27) revealed a Cronbach’s reliability coefficient of 0.86.
Self-Determination Theory, espoused by Deci and Ryan (1985, 1991) formed the basis of
the Learning Climate Questionnaire (LCQ). The LCQ was designed to measure the classroom
climate, specifically the autonomy support provided by the instructor (Deci & Ryan, 1985,
Williams & Deci, 1996). The LCQ short version, consisting of 6 questions, was used in this
research. Previous research assessed the reliability and validity of this instrument. Published
studies reported Cronbach’s alpha coefficients generally ranging above 0.90 (Black & Deci,
2000; Williams & Deci, 1996).
April 20-23, 2011
The target population consisted of students enrolled in two college of agriculture courses.
Both courses had a combined enrollment of 250 students. Of the 250 possible respondents, 212
respondents returned questionnaires, with four questionnaires incomplete or missing more than
five percent of responses. The four incomplete questionnaires were removed from the study
resulting in a useable sample of 208 respondents.
Data were analyzed using the PASW 17.0 statistical software package. Descriptive data
relating to the research objectives were analyzed to further describe verbal immediacy, nonverbal
immediacy, and student autonomy perceptions. Cohen’s d (Cohen, 1988) was also used to
measure the effect size of the mean values. Cohen defined effect sizes as small (.20-.50),
medium (.50-.80), and large (>.80). Effect sizes were calculated on mean values and those values
evidencing a small, medium or large effect size were noted. The data utilized in this research
were part of a larger research study.
Results/Findings
A demographic overview indicated the 208 respondents reported assessing 50 course
prefixes based on the course they attended immediately preceding the course in which collection
occurred. Of the 50 course prefixes, the largest categories were chemistry (n = 23, 11.1 %), math
(n = 20, 9.6%), animal science (n = 15, 7.2%), biology (n = 14, 6.7%) and rural sociology (n =
14, 6.7%). The remaining 45 categories were fairly evenly distributed with no single category
accounting for more that 5 percent of the respondents. The students represented a fairly
heterogeneous mix between grade levels with 21.6% freshmen, 23.6% sophomore, 33.7%
juniors, and 21.2% seniors. Regarding course type, respondents identified 20.7% of the classes
as elective and 78.4% as required.
April 20-23, 2011
Table 1
Student perceived verbal immediacy, nonverbal immediacy and autonomy in relation to
classroom variables
n
Elective
Required
43
163
Verbal
Immediacy
M SD
3.20 (.58)
2.79 (.77)
Lecture
Laboratory
Recitation
153
20
32
2.79 (.82)
2.77 (.76)
2.91 (.71)
3.63 (.64)
3.45 (.56)
3.40 (.65)
2.82 (.92)
3.06 (.86)
2.88 (.81)
Early Morning
Middle of the
Day
Late Afternoon
Evening
81
2.80 (.82)
3.61 (.69)
2.78 (.89)
82
2.81 (.75)
3.60 (.58)
2.92 (.90)
34
8
2.92 (.82)
2.29 (.67)
3.56 (.64)
2.96 (.49)
2.98 (.97)
2.46 (.68)
75
38
28
16
15
33
3.06 (.71)
2.90 (.77)
2.91 (.88)
2.49 (.80)
2.76 (.87)
2.23 (.53)
3.55 (.58)
3.51 (.79)
3.55 (.65)
3.65 (.64)
3.76 (.68)
3.58 (.55)
3.16 (.82)
2.93 (.90)
2.82 (.96)
2.65 (.81)
2.77 (1.14)
2.26 (.65)
Course Type
Nonverbal
Immediacy
M SD
3.78 (.48)
3.52 (.66)
Autonomy
M SD
3.13 (.82)
2.78 (.91)
Class Section
Class Time
Class Size
0-29
30-59
60-89
90-119
120-149
>150
Note. Scale: 1 = never to 5 = very often
Class section -- whether lecture, laboratory, or recitation – resulted in little mean
variation between verbal immediacy, nonverbal immediacy, or autonomy. Class time evidenced
a drop in verbal immediacy between late afternoon 2.92 (n = 34, SD = .82) and evening classes
2.29 (n = 8, SD = .67). The verbal immediacy difference resulted in a strong effect size of d =
.84. However, due to the small number of respondents (n = 8) in the evening category, the
results should be interpreted with caution.
Class size evidenced variation in mean values as well. Verbal immediacy was highest for
class sizes of 0-29 ( x = 3.19, n = 35, SD = .76) and decreased as class size increased for a verbal
immediacy mean score of 2.23 (n = 33, SD = .53) for a class size of 150 or more students. The
verbal immediacy effect size difference between a class size of 0-29 and 150 or more was strong
at d = 1.46.
April 20-23, 2011
Not surprisingly, nonverbal immediacy was fairly consisted despite changes in class size.
Autonomy, on the other hand, followed a pattern similar to verbal immediacy with a steady
decrease as class size increases. A class with the size of 0-29 had a mean value of 3.13 (n = 35,
SD = .92) and class sizes 150 or greater had a mean value of 2.26 (n=33, SD = .65), resulting in a
strong effect size of d = 1.09. Comparison between means based on class type (elective vs.
required) indicated that students rate the instructors of elective courses as higher in verbal
immediacy, nonverbal immediacy, and autonomy.
Table 2
Student perceived verbal immediacy, nonverbal immediacy and autonomy in relation to
instructor variables.
n
Professor
Graduate Student
159
46
Verbal
Nonverbal
Immediacy Immediacy
M SD
M SD
2.80 (.82)
3.63 (.62)
2.82 (.71)
3.39 (.66)
Male
Female
149
59
2.74 (.79)
2.98 (.76)
3.56 (.65)
3.63 (.61)
2.82 (.93)
2.98 (.81)
45
42
45
59
14
1
2.80 (.59)
2.80 (.79)
2.66 (.81)
3.13 (.79)
2.93 (.59)
--
3.35 (.69)
3.56 (.52)
3.50 (.66)
3.80 (.62)
3.66 (.51)
2.83 (.74)
2.81 (1.01)
2.63 (.95)
3.08 (.88)
2.99 (.79)
Instructor Type
Autonomy
M SD
2.82 (.92)
2.96 (.80)
Instructor Gender
Instructor Age
20-29
30-39
40-49
50-59
60-69
70 or more
The respondent means varied slightly on instructor age. There is a trend towards
increasing verbal immediacy means based on age with 20-29 year old professors evidencing a
mean of 2.53 (n = 9, SD = .64). The mean score increased with every age category, peaking at
age 50-59 with a mean of 3.07 (n = 59, SD = .78) and decreasing for age category 60-69 and 70
or more. Nonverbal immediacy evidenced an eerily similar trend beginning with an age 20-29
year old mean of 3.27 (n =9, SD = .82) increasing until 50-59 year old mean of 3.80 (n = 59, SD
= .62). Just like verbal immediacy, after the 50-59 year age category, nonverbal immediacy
began to taper off. Autonomy evidenced a similar trend with the exception of a mean values dip
in the age 40-49 category. There also appeared to only be a slight decrease in the autonomy mean
values of professors age 60-69.
April 20-23, 2011
Table 3
Student perceived verbal immediacy, nonverbal immediacy and autonomy in relation to student
variables.
N
Class Rank
Freshman
Sophomore
Junior
Senior
45
49
70
44
Verbal
Immediacy
M SD
2.57 (.75)
2.80 (.89)
2.89 (.73)
2.92 (.76)
Nonverbal
Immediacy
M SD
3.54 (.65)
3.63 (.61)
3.58 (.64)
3.52 (.76)
2.77 (.80)
2.87 (.76)
3.47 (.64)
3.77 (.57)
Autonomy
M SD
2.59 (.67)
2.84 (1.02)
2.96 (.90)
2.99 (.91)
Student Gender
Male
132
Female
76
2.81 (.87)
2.96 (.94)
The mean data for class rank evidenced several interesting descriptive trends. As
students move from freshman to senior they reported increased verbal immediacy. Freshman (n
= 45) reported verbal immediacy scores of 2.57 (SD = .75) and seniors (n = 44) report 2.92 (SD
= .76) yielding a small effect size of d = .46. Nonverbal immediacy evidenced no major mean
differences based on class rank. Autonomy, as might be expected, increased with class rank.
Freshman reported an autonomy mean of 2.59 (SD = .67) and seniors reported 2.99 (SD = .91)
for a moderate effect size of d = .50.
Table 4
Relationships between verbal immediacy, nonverbal immediacy and autonomy
Nonverbal Immediacy
Autonomy
a
*
Verbal Immediacy
Pearson Correlation
.60
.82*
Adjective b
Strong
Very High
a
Nonverbal Immediacy Pearson Correlation
-.54*
Adjective b
Moderate
a
b
Note. n = 208 Denotes independent variables. Adjectives according to Bartz, 1999.
* Correlation is significant at the 0.05 level (2-tailed).
Examination of the variables revealed a strong association between verbal and nonverbal
immediacy. Autonomy evidenced a very high associated with verbal immediacy and a moderate
association with nonverbal immediacy. Based on the recommendations of King and Minium
(2008) the correlational values were squared to determine the coefficient of determination (r2).
Results indicated that 29% of the variance in autonomy was explained by nonverbal immediacy
and 67% of the variance in autonomy was explained by verbal immediacy. In the relationship
between nonverbal and verbal immediacy, 36 % of the variance in verbal immediacy was
associated with nonverbal immediacy.
April 20-23, 2011
Conclusions & Recommendations
Objective one sought to describe the variables of interest based on classroom variables.
Comparison between means based on class type (elective vs. required) indicated that students
rate the instructors of elective courses as higher in verbal immediacy, nonverbal immediacy, and
autonomy-supportive behaviors. This seems philosophically sound as students who enroll in
elective courses may display a heightened sense of engagement, purpose, and belonging prior to
enrolling in the course. The predisposition towards the elective course may taint the
respondents’ observations of verbal, nonverbal, and autonomy-supportive behaviors. Another
plausible conjecture would be that elective classes may tend to have a smaller class size as well.
Smaller class sizes may, as previously discussed, tend to increase the incidence of both verbal
immediacy and autonomy-supportive behaviors.
The mean values for class section had little variation on reported verbal immediacy,
nonverbal immediacy, and autonomy. Instructors, as perceived by the respondents, display
similar levels of immediate and autonomy behaviors despite class section. This is an insightful
observation as instructors may tend to believe their opportunities for immediacy and autonomysupportive behaviors to vary based on class section. The results of this research indicate
relatively minimal differences between the three constructs and lecture, laboratory, and recitation
class sections.
Verbal immediacy and autonomy-supportive behaviors mean scores varied according to
class size. Nonverbal immediacy remained fairly stable despite class size variations. The
respondents reported a greater verbal immediacy and autonomy mean score relative to class sizes
from 0-29. As class size increased, mean values decreased. Results relating to class size
indicated that instructors engaged in teaching larger class sizes exhibited less verbal immediate
and autonomy-supportive behaviors. Previous research indicated that, specific to verbal
immediacy, instructors tended to compensate as class size increased, resulting in a stable verbal
immediacy score (Gorham, 1988). The present results do not fully support the previous research.
Several possible reasons for the observed mean value differences may exist.
One possible explanation may lie in the nature of small class sizes. Students engaged in
smaller classes may feel, by nature of the intimate classroom size and atmosphere, a closer
psychological relationship with the instructor. Students may be intimately involved in course
discussions, allowing for greater evidence of instructor verbal immediacy and autonomysupportive behaviors. Small class sizes seem to facilitate a greater display of verbal and
autonomy behaviors. Educators have long lauded the benefits of smaller class sizes, yet
universities recognize the fiscal benefit of larger class sizes. Perhaps university administrators
should consider which class size has the potential to provide the greatest educational and
motivational benefit to the students.
The second research objective sought to examine the variables of interest in relation to
instructor variables. The mean values of instructor age evidenced some variability between
verbal, nonverbal, and autonomy behaviors. Instructors did increase in verbal, nonverbal, and
April 20-23, 2011
autonomy-supportive behaviors through the age categories, peaking at 50-59 years of age. On all
three variables, instructors seemed to display the greatest verbal, nonverbal and autonomy
behaviors between 50 and 59 years of age. There may be several plausible reasons for this
observation.
First, the instructor age category which contained the highest number of respondents was
the 50-59 year age category. Perhaps, as the number of respondents in a given category increase,
the means tend to migrate upward. While the researchers did consider this possibility, the means
with sample sizes n=30 and n=45 do not increase markedly with instructor age, dispelling the
conjecture that sample size may act in a prescribed manner to increase the mean values of verbal,
nonverbal, and autonomy-supportive behaviors.
Another possible reason for the heightened display of verbal, nonverbal, and autonomy
behaviors may be the professional and personal state of the instructors. The research did not
assess whether the instructors were assistant, associate, or full professors. It can be reasonably
concluded that the majority of instructors in the 50-59 age category were tenured. Perhaps
tenured faculty feel the freedom to express themselves to a greater degree. If this is the case, it
may provide insight into how the nature of our current educational system has the ability to
impact students in the classroom. Further research should examine the impact of instructor age,
considering instructor tenure, in an effort to examine possible influences to the use of autonomysupportive behaviors.
Analysis of instructor gender revealed one interesting trend. Respondents assessing
female instructors reported higher mean values for verbal, nonverbal, and autonomy-supportive
behaviors. According to the student responses, female instructors exhibit a greater frequency in
the use of verbal, nonverbal, and autonomy-supportive behaviors. The differences between
instructors based on gender are small, yet female instructors appear to be more immediate and
autonomy-supportive. This may relate to the actual nature of the classroom instruction or the
results may be a byproduct of a societal view which portrays females as more verbal and more
caring than their male counterparts. Further research should be conducted to examine possible
immediacy and autonomy differences based on instructor gender.
Analysis based on the third research objective indicated that as students age they reported
encountering instructors with increasing levels of verbal immediacy. Freshman appeared to be
either less sensitive to verbal immediacy or the instructors of freshman courses less inclined to
display verbally immediate behaviors. Nonverbal immediacy was a fairly stable construct that
remained steady despite student age. Autonomy-supportive behaviors steadily increased with
student grade level.
Freshmen enter first year courses at a very vulnerable stage in their educational careers.
Therefore, instructors should make every effort to display positive, encouraging, and supportive,
verbal immediacy behaviors. Instructors need to be aware of nonverbal communication. Despite
student class rank differences, students seem to perceive similar amounts of nonverbal
immediacy. Instructors need to be aware of the influential nature of verbal immediacy and strive
to send supporting signals during the students’ formative years. Autonomy-supportive behaviors
April 20-23, 2011
seem to be employed by instructors more readily during the later educational years. Instructors
need to increase early opportunities for student autonomy, facilitating increased intrinsic interest
and motivation (Deci et al., 1991; Deci & Ryan, 2002).
The relationships between verbal immediacy, nonverbal immediacy, and autonomy were
positive, moderate to very high relationships. Prior research supports the relationship between
verbal and nonverbal immediacy (Frymier & Houser, 2000), and there are several theoretical
threads that unite autonomy and immediacy. Instructors should be encouraged to explore and
employ the use of autonomy-supportive and immediate behaviors. According to Reeve, Bolt, &
Cai (1999), autonomy supportive behaviors could be encouraged through the use of teacher
instructional behaviors which exert a significant influence on student feelings of autonomy
including: time spent talking, and time given to students for independent work. Teacher
conversational behaviors which enhance student autonomy include: praises of quality of
performance, questions of what the student wants, responses to student-generated questions and
empathetic, perspective-taking statements (Reeve et al., 1999). Instructors who take the time to
promote autonomy in the classroom will tend to develop autonomously motivated students.
Students who are autonomously motivated, according to Grolnick, Ryan, and Deci (1991), report
increased motivation to complete schoolwork, evidence greater conceptual learning, and greater
memory retention.
April 20-23, 2011
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April 20-23, 2011
A Descriptive Study of the Characteristics of Forestry Education in the Pacific Northwest
Ashley A. Reeves, Graduate Student
Kattlyn J. Wolf, Assistant Professor
University of Idaho
Abstract
The purpose of this study was to assess the current status of forestry education in high school
CTE programs in the Pacific Northwest (PNW). The PNW contains approximately 77.5 million
acres of forestland (National Association of State Foresters, 2008). Most current forestry
workers have no college education. This fact, combined with a projected 53,000 job openings in
the forestry industry create a career path for CTE graduates. However, little information is
available about the high schools and teachers offering forestry education. A researcher created
instrument was utilized to discover characteristics of teachers and programs offering forestry
education. Ninety nine teachers reported teaching forestry content in their courses; these
courses included Natural Resources courses, Forestry courses, Environmental Science courses
and Agricultural Science courses. The majority of teachers reported teaching forestry for more
than 10 years, with the most frequently taught topics being Fire Ecology and Resource
Management. Teachers also reported that their forestry curriculum developed leadership and
communication skills. Based on the findings of this study, the researchers recommend the results
of the study be provided to forest industry professionals and school administration to facilitate
the continued success of forestry education in the PNW.
Introduction & Literature Review
The forest industry is facing a, “growing shortage of qualified natural resource professionals
needed to fill positions vacated by retiring baby boomers” (Mason, 2005, p. 1). In 2003,
approximately 40% of employees in natural resource agencies were over the age of 50 (Lackey,
Nielsen, Rosen, Teich, and Day, 2004). In addition, 46% of permanent (as compared to
seasonal, part-time workers) United States Forest Service (USFS) employees were eligible to
retire in 2007, and those in the forester occupation comprised 49% of the employees eligible for
retirement (Lackey et al., 2004). The forest industry employs over 92,000 people in the United
States (USDL, 2008c). The Pacific Northwest (Oregon, Idaho & Washington) contains 30.5
million acres, 25.7 million acres, and 21.3 million acres of public and private forestland
respectively (National Association of State Foresters, 2008).
Future forestry workers must gain the training necessary for employment in the forest industry.
However, enrollment in university forestry programs is declining (Winistorfer, 2005).
Compounding this problem is the fact that students are interested in environmental issues, yet
have low interest in forestry careers (Hager, Straka, and Irwin, 2007). In the Pacific Northwest,
some high school Career and Technical Education (CTE) programs offer forestry curriculum to
train students for careers in the forest industry. However, little information is available about
schools that offer forestry courses, what content is taught, or the characteristics of the programs
and teachers that offer forestry related curriculum to high school students.
1
April 20-23, 2011
The need for forestry education arose in the early 19th century due to the rate of forest depletion
and the growing concern of a timber famine (Hosmer, 1923). At this time, it was suggested that
forest management was necessary in order to offset depletion of the nation‟s forest resources
(Miller & Lewis, 1999). The creation of the USFS resulted in new employees who now required
knowledge on how to manage public land (Miller & Lewis, 1999). This, combined with the
effects of the Morrill Act in 1862, which promoted applied agricultural education (Mobley,
1964), caused university forestry programs to sprout. The first of these was the establishment of
College of Forestry at Cornell University (Brown & Lassoie, 1998).
The Smith Hughes Act of 1917 brought federal funding for vocational education to the high
school level (Mobley, 1964). According to Tipton, Miller, and Kahler (1992), with the advent of
vocational education it was natural for instructors “to immediately incorporate forestry into their
curricula.” (p. 10). As early as 1943 in Oregon, the person who oversees the state department of
forestry, the State Forester, developed a 28 unit curriculum in conjunction with 5 other foresters
and Salem High School (Tipton et al., 1992). From that point forward forestry education was
offered through Career and Technical Education programs at the local level (Tipton et al., 1992).
In 1970, the state of Oregon officially created the first vocational forestry cluster program, with
statewide curriculum following suit in 1972 (Tipton et al., 1992).
Brown and Lassoie (1998) assert that because forestry is an applied science, it is “critical that
education of professional foresters correspond to the needs of potential employers…” (p. 8). A
study by Sample, Ringgold, Block, and Giltmier (1999) revealed that employers in the forest
industry place relatively high importance on forestry competencies like forest ecology, forest
inventory, species identification, and the manipulation of growth and species composition to
achieve landowner objectives, known as silviculture (Belt & Campbell, n.d.).
Employers also indicated that the most important skills were written and oral communication,
leadership, and problem solving skills (Sample et al., 1999). The curriculum of Career and
Technical Education programs should be centered around the skills and competencies needed by
the local and regional labor market (Roberts & Ball, 2009). CTE teachers offering education in
forestry topics must identify the skills and abilities necessary to prepare their students to find
gainful employment in the forest industry. In Oregon, forestry professionals reported that
forestry education should be part of the state‟s curriculum, but also reported a belief that the
school system was not adequately educating students on environmental issues (Tipton et al.,
1992). In order to ensure that students are being adequately prepared for the forestry industry, it
is important that Career and Technical Education programs train students to develop the skills
demanded by employers in the industry.
For the purposes of this study, the forest industry includes employees in the following
occupations: forester, forestry and conservation technician, forestry and conservation worker,
fallers, logging equipment operators, log graders and scalers, and all other logging workers.
These occupations are defined as follows: foresters manage forestlands; forestry and
conservation technicians compile data on forest tracts; forestry and conservation workers provide
manual labor to manage forestlands under supervision; fallers fell trees with axes or chainsaws;
logging equipment operators drive tractors or wheeled vehicles to fell, skid, load, or stack logs;
2
April 20-23, 2011
log graders and scalers inspect logs for defects and estimate their volume and value; and all other
logging workers are all logging workers not listed separately (United States Department of
Labor, 2008e).
In May 2008, employees working on forestland in Idaho, Oregon, and Washington totaled
17,800 (USDL, 2008a, USDL 2008b, and USDL 2008c). However, employment data for fallers,
logging equipment operators, and all other logging workers was not available in Idaho.
Additionally, data for forestry and conservation workers and log graders and scalers was not
available in Oregon. Idaho, Oregon, and Washington rank high in wages and employment
concentration in the forest industry when compared to the rest of the United States (USDL,
2008a, USDL 2008b, and USDL 2008c). Idaho‟s wages are the highest in the country for
graders and scalers, second for logging equipment operators, and fifth for all other logging
workers. Additionally, Idaho ranks first in employment concentration for all other logging
workers and third for foresters, forestry and conservation technicians, and logging equipment
operators (USDL, 2008a). Oregon‟s wages rank the highest in the country for all other logging
workers, third for logging equipment operators, and fifth for fallers (USDL, 2008b). Oregon also
ranks the highest in the nation in employment concentration of forestry and conservation
technicians and log graders and scalers (USDL, 2008b). Washington‟s wages rank the highest in
the nation for logging equipment operators, second for all other logging workers, fourth for
fallers and log graders and scalers, and fifth for foresters (USDL, 2008c). Washington also has
the third highest concentration of all other logging workers (USDL, 2008c).
According to the United States Department of Labor (2008e), 91% of forestry workers in the
U.S. have education below a Bachelor‟s Degree, and 75% of those had no college education
(UDSL, 2008e). This large number of minimal education level jobs makes the forestry industry
a possible career path for CTE graduates. Additionally, the forest industry is estimated to have
53,000 job openings between 2008 and 2018 (USDL, 2008f). The other component that makes
the forest industry viable for placement of CTE graduates are the family wage jobs that
employees in the industry earn. Marshall (1998) defines family wage as, “sufficient to maintain
a wife and children.” The national poverty line for a family of four with two children below the
age of 18 is $21,834 (United States Census Bureau, 2008). Nationally, the wages earned by
these employees are family wage jobs with the annual mean wage ranging from a low of $26,110
for Forest and Conservation Workers to a high mean of $55,040 for Foresters; creating an
average annual mean wage in the U.S. of $35,808 (USDL, 2008c). In Washington State, the
wages range from a low of $27,620 for Forestry and Conservation Workers to a high of $61,530
for Foresters with an average annual mean of $42,501(USDL, 2008d). Oregon ranges from a
low annual mean of $30,030 to a high of $60,120 for Foresters, with an average annual mean of
$42,661 across the industry (USDL, 2008b). In Idaho, the annual mean salaries range from a
low of $33,660 for Forest and Conservation Workers to a high of $61,000 for Foresters, resulting
in an average annual mean salary of $42,616 for all employees in the forest industry (USDL,
2008a). In Idaho, Oregon, and Washington annual salaries are higher than the national average.
People seeking employment in the forest industry in Idaho, Oregon, and Washington face
favorable job market conditions, including: minimal educational requirements, higher wages than
the national average, a projected increase in employment rates, and high attrition from the
ensuing retirement of baby boomers. However, it is unclear where the employees to fill these
3
April 20-23, 2011
jobs will come from in the future as enrollment in university forestry programs has been
declining (Luckert, 2006). The Pacific Northwest employs 30% of the nation‟s forest industry
workers (USDL, n. d.), and needs properly trained, competent workers to manage their forests.
Although some Career and Technical Education programs in Idaho, Oregon, and Washington
teach forestry curriculum to high school students, data about the number of programs, the content
offered in these programs and the characteristics of the programs and teachers is not readily
available. Therefore, this study is appropriate at this time to accurately provide the descriptive
information necessary for an accurate representation of high school forestry education in the
Pacific Northwest. This research supports the National Research Agenda for Agricultural
Education and Communication, Research Priority Area: Agricultural Education in School:
specifically increase access to agricultural education instruction and programming (Osborne,
n.d.). Forestry Education in the Pacific Northwest cannot be improved, nor can access to
forestry education be increased without a current and accurate assessment of the programs
offering forestry content.
Purpose & Objectives
Career and Technical Education programs in the Pacific Northwest. In order to achieve this
purpose, the following research questions were developed:
1. How many Career and Technical Education programs offer education in forestry in the
Pacific Northwest?
2. What forestry topics are taught in Career and Technical Education programs in the
Pacific Northwest?
3. Where do Career and Technical Education teachers in the Pacific Northwest obtain
content knowledge in forestry?
4. What leadership and communications skills are taught in courses containing forestry
topics in the Pacific Northwest?
Methods
A researcher created survey instrument was developed to gather information to answer the
research questions. The survey was field tested to ensure face and content validity with forestry
professionals, teacher educators, and high school forestry teachers in Montana. As the data
collected was descriptive in nature and in a unique population, a pilot test was not conducted. A
reliability analysis was not necessary as the instrument did not contain attitudinal measures and
only addressed personological and descriptive characteristics of the programs and teachers of
interest.
The State Departments of Education in Oregon, Idaho, and Washington identified high schools
that offer agricultural education, environmental science, natural resource sciences, and forestry
courses in order to ascertain which Career and Technical Education programs in the Pacific
Northwest (PNW) offer education in forestry (Idaho Department of Education, 2010;
Washington Department of Education, 2010; Oregon Department of Education, 2010). Of the
approximately 797 high schools offering Career and Technical Education programs in the PNW
4
April 20-23, 2011
27 schools in Idaho, 43 schools in Oregon, and 97 schools in Washington were identified as
schools that may potentially teach forestry curriculum.
The instructors at the identified schools were invited to participate in the survey following the
Total Design Method (Dillman, 2007). A personalized pre-notice email was sent to the
instructors informing them that they had been selected to participate in a research study. The
pre-notice email informed the teachers that by completing the survey they would be entered into
a drawing to win one of three $50 gift cards. One week following the pre-notice email, teachers
were emailed the link to the instrument using the on-line survey provider Survey Monkey®.
Fifty nine teachers responded to the first contact. One week later, a second email was sent out
requesting those teachers who had not completed the survey to do so; 20 responded to the second
contact. Three weeks after the initial contact, a follow-up email was sent requesting that teachers
who had not yet responded to do so; 17 responded to this contact. Two weeks later, the final
email contact was made and 8 responded to the survey. Those instructors who had still not
responded a week later were then mailed a hard copy of the survey; 32 responded yielding a final
response rate of 81%. Teachers who responded to the first two survey requests were considered
“on-time” respondents, while teachers who responded to later contacts were considered “late”
respondents. Non-response error was controlled by comparing on time respondents to late
respondents (Miller & Smith, 1983); there was no difference between the two groups and the
data were combined.
Findings
Career and Technical Education programs in the Pacific Northwest. One objective of this study
was to identify the number of Career and Technical Education programs offering education in
forestry, these data are presented in Table 1. In Idaho, 27 programs were identified by the Idaho
State Department of Education, however, four teachers indicated that they do not teach forestry
topics and two did not respond; resulting in 21 reported teachers in Idaho that teach forestry
curriculum. In Oregon, five teachers indicated that they do not teach forestry topics and 11 did
not respond; resulting in 27 total respondents offering forestry content in Oregon. In
Washington, 28 of the identified teachers indicated that they do not teach forestry topics and 18
did not respond to the survey; resulting in 51 teachers who teach forestry curriculum.
Table 1
CTE teachers in the Pacific Northwest teaching forestry curriculum (N = 167*)
Response
Yes
No
f
21
4
Idaho
(n = 25)
P
78
15
Oregon
(n = 32)
f
27
5
P
84
16
Washington
(n = 79)
f
P
51
65
28
35
Note. f = frequency, P = percentage; PNW = Pacific Northwest
* number of total CTE programs identified by State Departments of Education
5
April 20-23, 2011
PNW
(N = 136)
f
P
99
73
37
27
Teachers were asked to identify which of their classes contained forestry curriculum as shown in
Figure 1. In Washington, the class most frequently reported containing forestry curriculum was
Natural Resources (n = 45). In Oregon and Idaho, the most frequent response was a Forestry
class (n = 23, n =16 respectively), followed second by Natural Resources (n = 16, n = 11). Other
commonly cited courses teachers identified themselves as teaching that included forestry content
were Agricultural Science, Horticulture, and Plant Science.
Figure 1. Courses taught by CTE teachers containing forestry content (164 total courses were
identified).
In order to gain background information about the programs containing forestry content, teachers
were asked to indicate how long their school had been offering forestry curriculum (see Table 2).
The majority (51%) of teachers said their school had offered forestry for more than 10 years. Of
the remaining teachers, 17% indicated their school had been offering forestry content less than
five years, and 26% said the school had been offering forestry content for 5-10 years.
Table 2
Years that schools offered courses teaching forestry content (n = 99)
Time
< 5 years
5-10 years
11-20 years
21-30 years
31+ years
f
5
8
6
0
2
Idaho
(n = 21)
P
24
38
29
0
10
f
5
9
5
4
2
Oregon
(n = 25)
P
20
36
20
16
8
Washington
(n = 48)
f
P
7
15
9
19
17
35
10
21
5
10
Note. f = frequency, P = percentage; PNW = Pacific Northwest
6
April 20-23, 2011
PNW
(n = 99)
f
17
26
28
14
9
P
17
26
28
14
9
With regard to teacher experience, 23% of teachers reported teaching forestry content for less
than five years (see Table 3). The majority (63%) of teachers in the Pacific Northwest have
taught forestry education for 10 years or less. Six teachers in Idaho and three teachers in Oregon
have been teaching for over 20 years, but none of those teachers have been teaching forestry for
over 20 years. Washington was the only state with teachers who have experience with forestry
curriculum for more than 20 years.
Table 3
CTE Teachers years of teaching experience (n = 99)
Idaho
Oregon
Total
Teaching
Teaching
Forestry
Time
(n = 21)
(n = 20)
f/P
f/P
< 5 years
2/10
7/35
5-10 years
5/24
6/30
11-20 years
8/38
7/35
21-30 years
5/24
0/0
31+ years
1/5
0/0
Note. f = frequency, P = percentage
Total
Teaching
(n = 27)
f/P
10/27
8/22
6/16
2/5
1/3
Teaching
Forestry
(n = 26)
f/P
11/42
10/38
5/19
0/0
0/0
Washington
Total
Teaching
(n = 47)
f/P
9/19
7/15
16/34
13/28
2/4
Teaching
Forestry
(n = 48)
f/P
17/35
11/23
14/29
4/8
2/4
When asked where they obtained information related to forestry, more than 30% of teachers
reported that they gained between 0-10% of their knowledge of forestry from their college
education, the Cooperative Extension Service, a textbook, industry experience, or the internet
(see Table 4). A common „other‟ source noted by teachers was fellow agricultural instructors or
forestry teachers. For those reporting their college education as a source of information, 21% of
teachers indicated they gained 20-50% of their forestry related knowledge from their college
education. Information obtained from forestry professionals was cited by 37% of teachers as the
source of 20-50% of their overall knowledge of forestry.
Table 4
Sources of information for forestry curriculum (n = 97)
0-10%* 20-30%* 40-50%* 60-70%* 80-90%*
100%*
Information Source
f
P
f
P
f
P
f
P
f
P
f
P
College Education
38 39 31 32 10 10 10 10
0
0
1
1
Cooperative Extension
40 41 12 12
0
0
0
0
0
0
0
0
Forestry Professionals
22 23 35 36 11 11
5
5
3
3
0
0
Textbook
34 35 34 35
3
3
6
6
1
1
0
0
Industry Experience
34 35 16 16
8
8
4
4
4
4
0
0
Internet
33 34 23 24
5
5
1
1
0
0
0
0
Other
18 19
6
6
3
3
3
3
0
0
1
1
*teachers were asked what percentage of their knowledge was gained from these sources
7
April 20-23, 2011
One objective of this study addressed what specific forestry topics are taught in Career and
Technical Education programs in the Pacific Northwest. Resource management and fire ecology
were the most frequently taught subjects in the PNW (see Table 5). In Idaho, the most
frequently taught subjects were fire ecology, forest history, and forest policy. In Oregon,
compass and pacing were the most frequently taught subjects, followed by fire ecology and
forest policy. In Washington, resource management ranked the most frequent followed by both
social and political issues. While 40% of Oregon and 27% of Washington teachers include
chainsaw trouble shooting and maintenance, no teachers in Idaho reported teaching these topics.
Similarly, only six percent of Idaho teachers teach chainsaw use whereas 40% of those in Oregon
do, and 32% of teachers in Washington report teaching chainsaw use.
Table 5
Forestry related content taught in CTE courses
Idaho
(n = 31)
Content
f
P
Fire Ecology
27
87
Resource Management
20
65
Social Issues
21
68
Political Issues
21
68
Forest Policy
22
71
Compass and Pacing
19
61
Forest History
22
71
GPS
19
61
Harvesting
13
42
Fire Prevention
19
61
Prescribed Fire
17
55
Disease
15
48
Insects
12
39
Silviculture
15
48
Dendrology
14
45
Chainsaw Use
2
6
Aerial Photography
8
26
Chainsaw
0
0
Troubleshooting
Chainsaw Maintenance
0
0
Mensuration
6
19
(n = 164)
Oregon
(n = 60)
f
P
33
55
21
35
27
45
26
43
32
53
34
57
22
37
28
47
28
47
30
50
31
52
16
27
26
43
15
25
18
30
24
40
17
28
Washington
(n = 73)
f
P
46
63
65
89
56
77
54
74
43
59
42
58
46
63
42
58
41
56
32
44
32
44
41
56
34
47
41
56
35
48
23
32
21
29
PNW
(n = 164)
f
P
106
65
106
65
104
63
101
62
97
59
95
58
90
55
89
54
82
50
81
49
80
49
72
44
72
44
71
43
67
41
49
30
46
28
24
40
20
27
44
27
24
8
40
13
20
20
27
27
44
34
27
21
Classes in the PNW that contain less than 1 week of forestry curriculum totaled five percent (see
Table 6). The majority (71%) of classes have 1-18 weeks dedicated to forestry curriculum. Only
seven percent of Idaho courses and eight percent of Washington courses cover forestry
curriculum for 28-36 weeks. However, in Oregon, 40% of teachers spent 28-36 weeks on
forestry curriculum.
8
April 20-23, 2011
Table 6
Time devoted to forestry curriculum (n = 162)
Idaho
(n = 30)
Time
f
P
28-36 weeks
2
7
19-27 weeks
1
3
10-18 weeks
7
23
1-9 weeks
18
60
> 1 week
2
7
Oregon
(n = 53)
f
21
3
11
16
2
Washington
(n = 79)
f
P
8
10
4
5
18
23
45
57
4
5
P
40
6
21
30
4
PNW
(n = 162)
f
P
31
19
8
5
36
22
79
49
8
5
Teachers were asked if their forestry curriculum developed leadership skills. In total, 20 teachers
in Idaho, 23 teachers in Oregon, and 44 teachers in Washington indicated that their forestry
curriculum developed leadership skills. When asked to identify which leadership skills their
forestry curriculum developed, teachers from all three states in the PNW most frequently
identified problem solving as a skill developed through their forestry curriculum (see Table 7).
Teachers in the PNW (88%) also reported that team work was a leadership skill frequently
developed through forestry curriculum.
Table 7
Leadership skills developed through forestry curriculum (n = 147)
Idaho
Oregon
Washington
(n = 30)
(n = 54)
(n = 63)
f
P
f
P
f
P
Leadership Skill
Problem solving
Team work
Communication
Interpersonal Skills
Cooperation
Applying Ethical Principles
Time Management
Organization
27
26
19
24
19
15
15
15
90
87
63
80
63
50
50
50
45
44
40
39
42
36
35
35
83
81
74
72
78
67
65
65
63
59
56
48
50
47
46
44
100
94
89
76
79
75
73
70
PNW
(n = 147)
f
P
135
129
115
111
111
98
96
94
92
88
78
76
76
67
65
64
When asked specifically about communication skills, most teachers in the PNW identified their
curriculum as teaching the use of technology and listening skills (see Table 8). Use of
9
April 20-23, 2011
technology is reportedly taught by 94% of teachers in Washington, 75% of those in Oregon, and
76% of those in Idaho. Listening skills are taught by 90% of teachers in Washington, 77% of
those in Oregon, and 68% of those in Idaho.
Table 8
Communication skills developed through forestry curriculum (n = 150)
Idaho
(n = 25)
Communication skill
f
P
Use of technology
19
76
Listening
17
68
Public Speaking
15
60
Public Relations
10
40
Business Writing
6
24
Negotiation
7
28
Oregon
(n = 57)
f
P
43
75
44
77
38
67
32
56
23
40
23
40
Washington
(n = 68)
f
P
64
94
61
90
52
76
24
35
25
37
21
31
PNW
(n = 150)
f
P
126
84
122
81
105
70
66
44
54
36
51
34
Teachers were asked how many of their students had Supervised Agricultural Experience (SAE)
programs related to forestry. The majority (66%) of teachers reported that 0-10% of their
students had an SAE related to forestry (see Table 9). Only 10% of teachers reported that 70%
or more of their students had an SAE related to forestry. In Idaho, no teachers reported more
than 41% of their students having an SAE related to forestry. Comparatively, 8% of Washington
teachers reported 91-100% of their students having SAE‟s related to forestry.
Table 9
Students with SAE projects related to forestry (n = 145)
Idaho
Oregon
(n = 34)
(n = 32)
% SAE
f
P
f
P
0-10%
28
90
22
63
11-20%
4
13
1
3
21-30%
1
3
1
3
31-40%
1
3
0
0
41-50%
0
0
0
0
51-60%
0
0
2
6
61-70%
0
0
0
0
71-80%
0
0
5
14
81-90%
0
0
1
3
91-100%
0
0
0
0
10
April 20-23, 2011
Washington
(n = 79)
f
P
46
58
8
10
3
4
4
5
2
3
7
9
0
0
1
1
2
3
6
8
PNW
(n = 145)
f
96
13
5
5
2
9
0
6
3
6
P
66
9
3
3
1
6
0
4
2
4
Only 45% of teachers in the PNW indicated that their students participated in the FFA forestry
Career Development Event (CDE) (see Table 10). In Idaho, the majority (56%) of teachers
reported that they have between one and 10 students who participate in the Forestry CDE. Only
five teachers in Oregon have students who participate in the forestry CDE. Three Washington
teachers reported that they have more than 20 students participate in the CDE.
Table 10
Students who participated in the FFA Forestry CDE (n = 75)
Idaho
(n = 16)
f
P
Participants
31+
0
0
21- 30
0
0
11-20
3
19
1-10
9
56
Zero
4
25
Oregon
(n = 18)
f
0
1
2
2
13
P
0
6
11
11
72
Washington
(n = 41)
f
P
2
5
1
2
7
17
7
17
24
59
PNW
(n = 75)
f
2
2
12
18
41
P
3
3
2
2
55
Based on those teachers who reported that their students competed in the Forestry CDE, an
average of 13.74 students participated in the CDE in each program in the PNW (see Figure 2).
Oregon had the highest average number of students who competed (M = 16.4, SD = 8.5), but
also had the fewest number of teachers with students who participated. Washington‟s average
number of student participants was 15.5 (SD = 12.7). In Washington, the reported number of
students who participated in the Forestry CDE ranged from zero to as many as 55.
Figure 2. Average number of students who participated in the FFA forestry CDE
OR (M = 16.4, SD = 8.11); ID (M = 10, SD = 4.81); WA (M = 15.5, SD = 12.7); PNW (M =
13.7, SD = 9.8)
Conclusions & Recommendations
The Pacific Northwest employs one-third of the forest industry workers in the United States
(USDL, n.d.). Of those, 75% have no college education (USDL, 2008e); indicating that most
forest industry workers gain their professional knowledge either through their high school
11
April 20-23, 2011
education or on the job training. This represents significant job opportunities for high school
CTE graduates to pursue. Currently in the Pacific Northwest, 21 high schools in Idaho, 27 high
schools in Oregon, and 51 high schools in Washington offer education in forestry. These 99
schools offer 164 courses covering topics in forestry education.
Most teachers reported teaching forestry content for only a portion of their careers. This may
indicate that teachers moved into positions or schools where forestry education is taught, or they
developed a program after teaching in a school for some time. Since most teachers have not
been teaching forestry content their entire career, the researchers investigated where they
acquired the content information taught in their classes. Those teachers who gained a larger
proportion of information from a particular source frequently cited forestry professionals,
industry experience, and textbooks. Although the Cooperative Extension Service and internet
were reported quite frequently as sources for content, teachers also indicated that they gained a
much smaller percentage of their overall knowledge from these two sources. Several teachers
also indicated that they use other CTE teachers as resources. Teacher educators and college
forestry professors need to be aware of teachers‟ needs in forestry related content in order to
facilitate appropriate professional development experiences.
The most frequently taught forestry subjects in the Pacific Northwest varied from state to state.
Species identification, silviculture, and forest inventory were among the subjects taught the least
across the region; this is contradictory to industry recommendations (Sample et al., 1999; Belt &
Campbell, n.d.). The topics taught the most were fire ecology and resource management. The
researchers speculate that this is a reflection of the paradigm shift from traditional production to
ecology and resource management. In Washington, resource management, social issues, and
political issues were the three most frequently taught forestry topics. In Idaho, the top three were
fire ecology, forestry history, and forest policy. Oregon had a much more even distribution
among topics, but the most frequently offered were fire ecology, forest policy, and prescribed
fire. The major difference among states appeared in the area of chainsaws. Idaho offers little
curriculum in the way of chainsaw use, troubleshooting, and maintenance. However, in Oregon
and Washington nearly one third or more of teachers include chainsaw use, troubleshooting, and
maintenance in their curriculum.
In Idaho and Washington, the majority of teachers taught forestry content for less than 9 weeks.
Oregon teachers incorporated much more forestry curriculum; 40% of classes contain forestry
curriculum for 28-36 weeks. The emphasis on forestry education in Oregon may be a reflection
of the industry‟s influence and importance to the state. According to Sample et al. (1999), forest
industry employers highly value communication, leadership, and problem solving skills. Of
forestry courses in the Pacific Northwest, nearly all the teachers reported that their curriculum
developed communication and leadership skills. CTE teachers are clearly working to meet forest
industry demands, however only 36% of classes develop business writing skills. Many more
teachers reported that their classes developed oral communication skills such as public speaking
and public relations. High school instructors and teacher educators need to ensure that high
school students receive an education that prepares them to enter the forest industry upon
graduation from high school.
12
April 20-23, 2011
Based on these findings, the researchers recommend a follow-up study of forestry education in
the Pacific Northwest. The curriculum and content offered in other states with timber interests
should be addressed in the follow-up study. The researchers were unable to locate current data
on employability skills desired by the forestry industry; the most recent information available
was over 10 years old (Sample et al., 1999). Therefore, the researchers recommend that the
results of the present study be made available to forestry professionals, with the encouragement
to complete a follow-up study of employability skills.
In the present study, teachers were only asked to report how much total time was devoted to
forestry curriculum in their classes; as opposed to time devoted to each content area. Future
studies should address how much time is devoted to each subject area within forestry. Finally,
the results of any future studies should be made available to forest industry and school
professionals. Communication between forestry professionals, teacher educators, and high
school instructors is important for adequately training high school students for today‟s forest
industry. The researchers recommend that a database be created of CTE teachers who teach
forestry content to help facilitate information and resource sharing amongst teachers. Teachers
and administrators would benefit from a realistic depiction of forestry education; while industry
professionals could both benefit from and assist in the improvement of forestry education in the
Pacific Northwest.
13
April 20-23, 2011
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Miller, C. & Lewis, J. G. (1999). A contested past: Forestry education in the United States, 18981998. Journal of Forestry, 97(9), 38-43.
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45-50.
Mobley, M. D. (1964). A review of federal vocational-education legislation 1862-1963. Theory
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Retrieved from http://www.ode.state.or.us/data/stats/opte/apprprgs.aspx
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Osborne, E. W. (Ed.) (n.d.). National research agenda: Agricultural education and
communication, 2007-2010. Gainesville, FL: University of Florida, Department of
Agricultural Education and Communication.
Roberts, T. G., & Ball, A. L. (2009). Secondary agricultural science as content and context for
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Sample, V. A., Ringgold, P. C., Block, N. E., & Giltmier, J. W. (1999). Forestry education:
Adapting to the changing demands on professionals. Journal of Forestry, 97(9), 4.
Tipton, G. M. III, Miller, W. W., & Kahler, A. A. (1992). Professional forester perceptions of
the value of forestry education in high schools (Journal Paper No. J-14499). Iowa.
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Number of Related Children Under 18 Years. Retrieved from
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/may/oes_id.htm
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Wage Estimates Oregon. Bureau of Statistics. Retrieved from http://www.bls.gov
/oes/2008/may/oes_or.htm
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Winistorfer, P. M. 2005. Competitiveness, Manufacturing, and the Role of Education in the
Supply Chain for the Forest Industry. Forest Products Journal, 55(6), 6-16.
16
April 20-23, 2011
A Multi-State Factor-Analytic and Psychometric Meta-Analysis of Agricultural Mechanics
Laboratory Management Competencies
Billy McKim, Texas A& M University
P. Ryan Saucier, Texas State University, San Marcos
Abstract
For more than 20 years, the 50 agricultural mechanics laboratory management competencies
identified by Johnson and Schumacher in 1989 have served as the basis for numerous needs
assessments of secondary agriculture teachers. This study reevaluated Johnson and
Schumacher’s instrument, as modified by Saucier, Schumacher, Funkenbusch, Terry, and
Johnson (2008), to reduce the number of competencies and update the constructs of agricultural
mechanics laboratory management competencies through factor-analytic and psychometric
analyses. Five-hundred and three in-service secondary agriculture teachers from six states,
surveyed between the spring of 2008 and the spring of 2010, served as the population for this
study. As a result, the 70 agricultural mechanics laboratory management competencies included
in the instrument modified by Saucier et al. (2008) were reduced to 33 competencies, in eight
constructs. A further outcome was reflected in the psychometric evaluation of the eight
constructs, which resulted in acceptable internal consistency reliabilities that ranged from .82 to
.96. Multi-state benchmarks for agricultural mechanics laboratory management abilities of
secondary agriculture teachers were also proposed. The results further indicated that the revised
constructs were appropriate to assess agricultural mechanics laboratory management
competencies across all five teacher career stages.
Introduction
Laboratories are essential learning environments for quality secondary agriculture
programs (Baker, Thoron, Myers, & Cody, 2008; Thoron & Myers, 2010). A review of literature
identified that much of the instruction within the secondary agricultural mechanics curriculum
takes place in a laboratory setting (Johnson & Schumacher, 1989; McKim, Saucier, & Reynolds,
2010; Saucier & McKim, 2010a; Saucier, Terry, & Schumacher, 2009)—in some states, nearly
60% of the curriculum taught in agriculture courses included agricultural mechanics
competencies (McKim et al., 2010). Furthermore, Saucier et al. (2009) found that Missouri
agricultural educators spent almost 10 hours per week supervising students in an agricultural
mechanics laboratory. With the frequent use of laboratories by agricultural educators, the need
for safe and effective laboratory instruction seems apparent.
For safe and effective laboratory instruction to take place, agricultural educators must be
competent and knowledgeable in the area of laboratory management (Saucier et al., 2009).
Hubert, Ullrich, Lindner, and Murphy (2003) stated, ―
if skill development is the focus of
laboratory instruction, then thorough attention to all its components, including safety instruction,
is essential‖ (p. 3). Fletcher and Johnson (1990) found that agricultural mechanics students are
exposed to equipment, materials, tools, and supplies that are potentially hazardous to their health
and could cause injury or death. Additionally, Phipps, Osborne, Dyer, and Ball (2008) noted that
the agriculture teacher is responsible for identifying safety hazards, providing daily safety
April 20-23, 2011
instruction, and maintaining safe working conditions for students in an agricultural mechanics
laboratory.
Considering the amount of instructional time spent in agricultural mechanics laboratories
across the U.S., it is critical that a needs assessment be conducted to determine the agricultural
mechanics laboratory management needs of secondary agriculture teachers. To do so, a valid and
reliable data collection instrument must be used to accurately gauge the agricultural mechanics
laboratory management abilities of secondary agriculture teachers.
In 1989, Johnson and Schumacher identified 50 agricultural mechanics laboratory
management competencies to assess the agricultural mechanics laboratory management abilities
of secondary agriculture teachers. In the more than 20 years since Johnson and Schumacher
identified those competencies, numerous studies (Johnson, Schumacher, & Stewart, 1990;
McKim et al., 2010; Saucier & McKim, 2010a; Saucier & McKim, 2010b; Saucier, Schumacher,
Funkenbusch, Terry, & Johnson, 2008; Saucier et al., 2009; Schlautman & Shilletto, 1992; Swan,
1992) have been conducted using some iteration of the instrument. In 2008, Saucier et al.
modified Johnson and Schumacher’s instrument to split multiple-component—double-barreled
and triple-barreled—competencies into single-component competencies. Thus, the original 50
competencies were expanded to 70 competencies.
Theoretical Framework
Bandura’s theory of self-efficacy (1997) was used to guide this study. According to
Bandura, self-efficacy is defined as the ―
beliefs in one’s capabilities to organize and execute the
course of action required to produce given attainments‖ (p. 3). Additionally, self-efficacy
influences a person’s choices, actions, the amount of effort they give, how long they persevere
when faced with obstacles, their resilience, their thought patterns and emotional reactions, and
the level of achievement they ultimately attain (Bandura, 1986).
In 2008, Knoblock found that the predetermined beliefs of teachers often influence how
they connect academic content in the classroom to real-life applications in the laboratory.
According to a review of literature, these beliefs are developed in part to personal beliefs about
the curriculum or content (Borko & Putnam, 1996; Moseley, Reinke, & Bookout, 2002; Pajares,
1992), availability of time, availability instructional resources, level of preparation regarding the
content (Thompson & Balschweid, 1999), comfort level with the content, (Knobloch & Ball,
2003), perceived value of the content (Lawrenz, 1985), past experiences with the content area
(Calderhead, 1996; Thompson & Balschweid), teaching environment (Knobloch, 2001), and
motivation (Bandura, 1997; Tschannen-Moran, Woolfolk-Hoy, & Hoy, 1998). A teacher’s
development and performance can also influenced by the interaction of these personal and
environmental factors and the situations in which they teach (Knobloch, 2001).
Purpose and Research Objectives
Numerous studies regarding agricultural mechanics needs assessment (McKim et al.,
2010; Saucier & McKim, 2010a; Saucier & McKim, 2010b; Saucier et al., 2008; Saucier et al.,
2009; Schlautman & Shilletto, 1992; Swan, 1992) have been conducted using some iteration of
April 20-23, 2011
the instrument developed by Johnson and Schumacher (1989). Those studies have provided
guidance for the profession and for the advancement of agricultural mechanics in secondary and
post-secondary settings.
Since 1989, Johnson and Schumacher’s instrument has been modified and revised by
researchers for various reasons, e.g. double- and triple-barreled questions, etc. By expanding the
original 50 competencies to 70, subjects were asked to answer no less than 140 questions; for
each competency, they were asked to assess the importance of the competency and their ability
to perform it. The length of a questionnaire has been noted to have an effect on item response
rates, accuracy of data collected, and individuals’ willingness to participate, in both mailed
(Dillman, Sinclair, & Clark, 1993) and web-based (Galesic & Bosnjak, 2009) surveys. Thus,
reducing the number of items, while retaining as much of the original information as possible
(Field, 2009), would likely increase the willingness of individuals to participate in the survey,
increase item response rates, and the accuracy of data collected (Dillman, et al.; Galesic &
Bosnjak)—a task often accomplished through factor-analytic and psychometric analyses (Field).
A review of the literature did not yield an obvious factor-analytic or psychometric analysis of
Johnson and Schumacher’s original competencies or the expanded version (Saucier et al., 2008),
in the more than 20 years since the original instrument was developed. Given the major revisions
and expansions to the instrument and the extended amount of time elapsed since the previous
assessment, a reassessment of Johnson and Schumacher’s instrument, as revised, was warranted.
Moreover, a validation and reassessment of the reliability of a data collection instrument
to be used to accurately gauge the agricultural mechanics laboratory management abilities of
secondary agriculture teachers, meets one of the research priorities listed in the National
Research Agenda of Agricultural Education and Communication (Osborne, n.d.). Under ―
RPA 4:
Prepare and provide an abundance of fully qualified and highly motivated agricultural educators
at all levels‖ (p. 8), the question was posed, ―
What are the professional development needs of
agricultural educators?‖ (p. 8). The outcome of this study will provide a more succinct and
accurate measure of secondary agriculture teachers’ professional development needs as related to
agricultural mechanics laboratory management.
Therefore, the purpose of this study was to reevaluate the instrument developed by
Johnson and Schumacher (1989), as modified by Saucier et al. (2008), and propose multi-state
benchmarks for in-service secondary agriculture teachers. This study was guided by three
research objectives:
1. Assess the factor-analytic and psychometric properties of the agricultural mechanics
laboratory management instrument, based on the perceptions of secondary agriculture
teachers regarding the importance of agricultural mechanics laboratory management
competencies.
2. Describe the self-perceived agricultural mechanics laboratory management abilities of
secondary agriculture teachers, to propose multi-state benchmarks for agricultural
mechanics laboratory management competencies.
3. Using the construct outcomes of the factor-analytic and psychometric analyses included
in Objective 1, determine if the self-perceived agricultural mechanics laboratory
management abilities of secondary agriculture teachers differ by teacher career stage.
April 20-23, 2011
Method and Results
Given the number of studies that have been conducted using some iteration of Johnson
and Schumacher’s instrument (1989), including studies of pre-service and in-service secondary
agriculture teachers, a meta-analytical approach was used for this study. ―
Meta-analysis is a form
of secondary analysis of pre-existing data that aims to summarize and compare results from
different studies (Newton & Rudestam, 1999, p. 281). Furthermore, meta-analyses ―
serve to
combine results from multiple studies and, consequently, allow us to diminish our reliance on
statistical tests from individual studies‖ (p. 281). Therefore, a form of meta-analysis was
conducted by including the results of studies conducted across six states within a two year
period.
Conflicting findings existed in the literature regarding the effect of developmental stages
of teachers on teacher efficacy (Burris, McLaughlin, McCulloch, Brashears, & Fraze, 2010;
Layfield & Dobbins, 2002). Therefore, teacher career stage was considered to be a variable of
interest. Thus, Huberman’s (1989) Teacher Career Cycle Model (TCCM) provided guidance in
the analysis of the data for this study. Within Huberman’s model, teacher career stage is divided
into five phases: Career entry-discovery and survival (1 to 3 years), stabilization (4 to 6 years),
experimentation/diversification (7 to 18 years), serenity (19 to 30 years), and disengagement (31
years and beyond).
Instrumentation
The instrument developed by Johnson and Schumacher (1989) included 50 competencies
developed with input from a national panel of agricultural mechanics education experts, through
a Delphi technique. The 50 item instrument was again used by Johnson (1989) to assess
secondary agriculture teachers’ perceptions of importance of agricultural mechanics laboratory
management competencies. As part of his study, Johnson conducted a principal component
analysis with a varimax rotation to assess the statistical validity of his instrument, which yielded
a five factor solution capable of explaining 46% of the variance. Johnson reported reliability
estimates (Cronbach’s α) that ranged from .63 to .88. Johnson and Schumacher’s instrument was
later modified by Johnson, Schumacher, and Stewart (1990) to include a double-matrix format to
assess the perceived importance of each competency and the perceived ability of the individual
to perform each competency. The instrument was again modified by Saucier et al. (2008) who
expanded the original 50 competencies to 70 competencies, as previously noted.
Data for this study were collected using the instrument developed by Johnson and
Schumacher (1989), as modified to include 70 competencies by Saucier et al. (2008).
Modifications to the design and format of the data collection instrument were guided by
Dillman’s (2007) suggestions. In the two-section data collection instrument, subjects were asked
to respond to 70 statements representing agricultural mechanics laboratory management
competencies, presented in a double-matrix configuration. The 5-point summated rating scale in
a double-matrix configuration allowed subjects to respond to each statement twice; once rating
the perceived importance of each competency (1 = No Importance, 2 = Below Average
Importance, 3 = Average Importance, 4 = Above Average Importance, 5 = Utmost Importance),
and once rating the individual’s ability to perform each competency (1 = No Ability, 2 = Below
Average Ability, 3 = Average Ability, 4 = Above Average Ability, 5 = Exceptional Ability).
April 20-23, 2011
Prior to data collection, a panel of eight experts was asked to assess face and content
validity of the instrument. Each member of the panel was considered an expert in the areas of
agricultural education, agricultural systems management, instrument development, and/or
research methods. A pilot test was conducted using individuals not selected in the samples for
the study. Initial estimates of reliability of the instrument were calculated using the results of the
pilot test, which yielded Cronbach’s alpha coefficients for the importance and ability scales that
ranged from .95 to .97 (n = 30).
Population
Data included in this study were collected from in-service secondary agriculture teachers
in six states between the spring of 2008 and the spring of 2010 (see Table 1). Data collection
efforts were made independently in each state. In each data collection effort, five points of
contact were attempted (Dillman, Smyth, & Christian, 2009). Because of the nature of a metaanalysis—combining data from multiple studies—the objectives of this study were not
inferential in nature. A more extensive description of the population (N = 503), including state,
population of secondary agriculture teachers in each state, sample size, and semester of data
collection, is provided in Table 1. Table 2 provides an overview of the secondary agriculture
teachers’ experience and the corresponding stage of teacher career cycle as defined by Huberman
(1989), which served as one basis of comparison for analyses.
Table 1
Description of Secondary Agriculture Teachers in Multi-State Agricultural Mechanics
Laboratory Management Studies from 2008-2010 (N = 503)
State
N
n
Semester of Data Collection
Arkansas
267
80
Spring 2009
Kentucky
247
87
Spring 2010
Missouri
424
110
Fall 2008
Oklahoma
436
111
Spring 2009
Tennessee
317
78
Spring 2010
Wyoming
47
37
Spring 2008
Table 2
Characteristics of Secondary Agriculture Teachers in Multi-State Agricultural Mechanics
Laboratory Management Studies from 2008-2010 (N = 503)
Stage of Teacher Career Cyclea
Yrs. Exper.b
1
2
3
4
5
State
M
SD
f
%
f
%
f
%
f
%
f
Arkansas 13.5 10.1
14 17.7 15 19.0
23 29.1
23 29.1
4
Kentucky 12.1
9.0
15 18.1 14 16.9
35 42.2
14 16.9
5
Missouri 12.2
9.2
23 20.9 15 13.6
44 40.0
23 20.9
5
Oklahoma 14.9 10.2
11 13.3 12 14.5
29 34.9
25 30.1
6
Tennessee 15.1 10.9
9
11.5
8
10.3
35 44.9
23 20.9
5
Wyoming 11.9
9.5
7
18.9
7
18.9
13 35.1
9 24.3
1
Total 13.3
9.8
79 16.8 71 15.1 179 38.1 108 23.0 33
Note: a Huberman, 1989; b Mean number years of secondary agricultural education teaching
experience.
April 20-23, 2011
%
5.1
6.0
4.5
7.2
4.5
2.7
7.0
Data Analyses
Data analyses were guided by the recommendations of Newton and Rudestam (1999)
regarding meta-analyses. All analyses were conducted using SPSS® version 17.0 for
Windows™ platform computers. Prior to analyses, data were screened. Those who completed
less than 50% of the instrument and who completed fewer than 50% of the items composing any
factor were eliminated, resulting in 503 useable responses. Furthermore, because a meta-analysis
requires combining data from multiple studies, before combining data collected during different
semesters and in different states, a multivariate analysis of variance (MANOVA) was used to
compare the initial variables of interest (importance, ability, state, and semester of data
collection) and determine compatibility of data for the meta-analysis. A MANOVA is the
appropriate analysis when ―
multiple independent and/or dependent variables and the measured
variables are likely to be dependent on each other (i.e., to correlate)…. Thus, multivariate
analysis allows for the examination of two variables while simultaneously controlling for the
influence of the other variables on each of them‖ (Newton & Rudestam, 1999, p. 137).
Box’s test of equality of covariance was not significant (semester of data collection, p =
.44; state, p = .09), which was an indicator that the assumption of equality of covariance was not
violated (Field, 2009). The results of the MANOVAs were interpreted using Wilks’ lambda (Λ).
There was not a significant effect of semester of data collection on the dependent variables
(importance and ability) Λ = .99, F(6, 930) = .62, p = .71, ηp2 = .004. Also, there was not a
significant effect of state on the dependent variables (importance and ability) Λ = .97, F(10, 926)
= 1.25, p = .26, ηp2 = .013. Thus, semester of data collection and state did not affect the data;
therefore, it was appropriate to combine the 503 responses to address the objectives of this study
and propose multi-state benchmarks for agricultural mechanics laboratory management
competencies. Additionally, these benchmarks may be used as a basis of comparison, to assess
agricultural mechanics laboratory management competency of secondary agriculture teachers.
Common methods variance (CMV) has been routinely noted as a pervasive problem in
social science research, ―
one that undermines good science and biases empirical conclusions‖
(Lance, Dawson, Birkelbach, & Hoffman, 2010, p. 436). CMV is important when involving selfreported measures, such as collecting independent variables and dependent variables via the
same method; e.g. self-administered questionnaire. Among the various methods of assessment
reported to be effective in controlling for CVM (e.g. Harmon’s single factor test, partial
correlation, etc.) those based on factor analysis tend to be the most rigorous (Meade, Watson, &
Kroustalis, 2007). Therefore, a principal component analysis was conducted, using SPSS®
version 17.0 for Windows™ platform computers, as a method for controlling CVM. Field’s
(2009) outline of methods for analyses and interpretation of the data served as the primary
guidance for the exploratory factor analysis. Tabachnick and Fidell (2007) served as a secondary
source of guidance.
Objective 1
The purpose of Objective 1 was to assess the factor-analytic and psychometric properties
of the agricultural mechanics laboratory management instrument, based on the perceptions of
secondary agriculture teachers regarding the importance of agricultural mechanics laboratory
April 20-23, 2011
management competencies. Hence, 70 importance scale items from the instrument revised by
Saucier et al. (2008) were included in the principal component analysis using a varimax rotation;
coefficients with an absolute value less than .45 were suppressed to eliminate double-loadings.
The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .95 and the Bartlett test of
sphericity was significant (p < .001). All commonalities were greater than .48. Field (2009) noted
that KMO values above .90 are considered to be superb; therefore, data were suitable for factor
analytic procedures.
Sixteen items were not included in the components because they had coefficients with an
absolute value less than .45. Six items were removed, because they loaded in components
consisting of less than three items. Cronbach’s alpha coefficients associated with the eight
components were calculated and ranged from .82 to .95 (n = 457). According to Field (2009),
alpha coefficients of .80 or greater are considered to be acceptable. Therefore, six components,
consisting of 15 items, were removed, because the associated alpha coefficients were less than
.80. The remaining 33 items composed the eight-component solution that accounted for 73.15%
of the total variance; components were then treated as independent constructs and served as the
dependent variables for the study. Eigenvalues, percentages of variance, cumulative percentages,
and Cronbach’s alpha coefficients for each construct are reported in Table 3. Construct loadings
from the principal component analysis of the items are reported in Table 4.
Table 3
Eigenvalues, Percentages of Variance, and Cumulative Percentages for Constructs
Eigenvalue
% of variance
Cumulative %
Cronbach's
Construct 1
3.897
11.808
11.808
.887
Construct 2
3.685
11.167
22.975
.853
Construct 3
3.130
9.485
32.461
.858
Construct 4
3.059
9.271
41.732
.875
Construct 5
2.802
8.491
50.222
.953
Construct 6
2.685
8.135
58.358
.957
Construct 7
2.612
7.916
66.273
.836
Construct 8
2.269
6.877
73.150
.823
Table 4
Construct Loadings from Principal Component Analysis with Varimax Rotation
Item
Construct 1: Hazardous Material Management
Loading
Safely storing hazardous materials
Safely disposing of hazardous materials
Safely handling hazardous materials
Properly installing and maintaining safety devices and emergency equipment
Correcting hazardous laboratory conditions
Construct 2: Laboratory Equipment Maintenance
0.820
0.817
0.803
0.521
0.479
Making minor repairs to the agricultural mechanics laboratory facility
Making minor agricultural mechanics lab equipment repairs
0.622
0.617
April 20-23, 2011
Table 4
Construct Loadings from Principal Component Analysis with Varimax Rotation
Item
(continues)
Loading
Performing routine maintenance of agricultural mechanics lab equipment
Installing stationary power equipment
Utilizing technical manuals to order replacement/repair parts for agricultural
mechanics lab equipment
Construct 3: Curriculum and Lesson Development
0.611
0.579
Maintaining a file of educational projects/activities for students
Developing a file of educational projects/activities for students
Selecting current references/technical manuals
Identifying current references/technical manuals
Construct 4: Program Public Relations and Recruitment
0.790
0.772
0.561
0.522
Implementing student recruitment activities for the agricultural mechanics
program
Planning student recruitment activities for the agricultural mechanics program
Conducting an agricultural mechanics public relations program
Planning an agricultural mechanics public relations program
Construct 5: Student Behavior Management
0.484
0.834
0.829
0.721
0.694
Maintaining a student discipline policy
Enforcing a student discipline policy
Developing a student discipline policy
Construct 6: Laboratory Activity Preparation
0.839
0.800
0.792
Identifying equipment required to teach agricultural mechanics skills
Identifying tools required to teach agricultural mechanics skills
Identifying supplies required to teach agricultural mechanics skills
Construct 7: Laboratory Facility and Program Management
0.781
0.749
0.721
Developing an agricultural mechanics laboratory budget
Operating within the constraints of an agricultural mechanics budget
Estimating time required for students to complete projects/activities
Maintaining computer based student academic records
Promoting laboratory safety by color coding equipment/marking safety
zones/posting appropriate safety signs and warnings
Developing objective criteria for evaluation of student projects/activities
Construct 8: Personal Protection Equipment Management
0.709
0.621
0.517
0.508
Storing protective equipment for student use
Maintaining protective equipment for student use
Selecting protective equipment for student use
0.748
0.705
0.658
April 20-23, 2011
0.471
0.462
According to Field (2009), individual items should measure the same underlying
dimension, in this case, agricultural mechanics laboratory management competencies. Field
noted that intercorrelations should range between ―
about .3‖ to no higher than .80 (p. 648). ―
If
any variables have lots of correlations below.3 then consider excluding them‖ (p. 648).
Intercorrelations greater than .80 could indicate issues related to multicolinearity, thus, those
items should be removed as well. None of the remaining 33 items had an associated correlation
scores less than .30 or greater than .80 (see Table 5). Similarly, constructs should correlate, even
if measuring different aspects of the same thing. One bivariate correlation score of .23 existed
between constructs 4 and 5; however, the constructs were not eliminated, because one low
correlation among 27 acceptable bivariate correlations was not considered sufficient cause to
eliminate the constructs.
Table 5
Bivariate Correlations Between Constructs
Construct
1
2
3
1
—
2
.498
—
3
.388
.640
—
4
.331
.439
.456
5
.467
.537
.413
6
.485
.669
.507
7
.471
.670
.610
8
.548
.472
.359
4
—
.227
.367
.444
.382
5
—
.568
.583
.415
6
—
.606
.430
7
8
—
.470
—
Objective 2
The purpose of Objective 2 was to describe the self-perceived agricultural mechanics
laboratory management abilities of the 503 secondary agriculture teachers to propose multi-state
benchmarks for agricultural mechanics laboratory management competencies. Hence, mean,
median, and standard deviation for secondary agriculture teachers’ perceived ability to perform
each agricultural mechanics laboratory management competency are reported in Table 6, by
construct.
Table 6
Mean Scores for Agriculture Teachers’ Abilities to Perform Competencies by Construct
Ability
Item
M
SD
Mdn
Construct 1: Hazardous Material Management
Safely handling hazardous materials
3.95
0.82
4.00
Safely storing hazardous materials
3.88
0.87
4.00
Correcting hazardous laboratory conditions
3.79
0.81
4.00
Properly installing and maintaining safety devices and emergency
equipment
3.73
0.83
4.00
Safely disposing of hazardous materials
3.70
0.93
4.00
Making minor agricultural mechanics lab equipment repairs
3.78
0.86
4.00
(continues)
April 20-23, 2011
Table 6
Ability
Item
M
SD
Mdn
Performing routine maintenance of agricultural mechanics lab
equipment
3.75
Utilizing technical manuals to order replacement/repair parts for
agricultural mechanics lab equipment
3.66
Making minor repairs to the agricultural mechanics laboratory facility
3.61
Installing stationary power equipment
3.50
Construct 3: Curriculum and Lesson Development
0.85
4.00
0.84
0.87
0.90
4.00
4.00
3.00
0.83
0.82
0.76
0.78
3.00
3.00
3.00
3.00
3.38
0.84
3.00
3.31
3.14
3.12
0.83
0.85
0.80
3.00
3.00
3.00
Enforcing a student discipline policy
3.98
Developing a student discipline policy
3.96
Maintaining a student discipline policy
3.96
Construct 6: Laboratory Activity Preparation
0.85
0.82
0.82
4.00
4.00
4.00
Identifying tools required to teach agricultural mechanics skills
3.93
Identifying equipment required to teach agricultural mechanics skills
3.90
Identifying supplies required to teach agricultural mechanics skills
3.87
Construct 7: Laboratory Facility and Program Management
0.81
0.80
0.79
4.00
4.00
4.00
Maintaining computer based student academic records
Operating within the constraints of an agricultural mechanics budget
Developing objective criteria for evaluation of student projects/activities
Developing an agricultural mechanics laboratory budget
Estimating time required for students to complete projects/activities
Promoting laboratory safety by color coding equipment/marking safety
zones/posting appropriate safety signs and warnings
3.72
3.63
3.57
3.56
3.42
0.92
0.90
0.76
0.86
0.82
4.00
4.00
4.00
3.00
3.00
3.42
0.88
3.00
Maintaining a file of educational projects/activities for students
3.45
Developing a file of educational projects/activities for students
3.44
Identifying current references/technical manuals
3.34
Selecting current references/technical manuals
3.31
Construct 4: Program Public Relations and Recruitment
Planning student recruitment activities for the agricultural mechanics
program
Implementing student recruitment activities for the agricultural
mechanics program
Conducting an agricultural mechanics public relations program
Planning an agricultural mechanics public relations program
Construct 5: Student Behavior Management
April 20-23, 2011
(continues)
Table 6
Ability
Item
M
SD
Mdn
Construct 8: Personal Protection Equipment Management
Selecting protective equipment for student use
4.13
0.73
4.00
Maintaining protective equipment for student use
3.86
0.79
4.00
Storing protective equipment for student use
3.76
0.79
4.00
Note: 1 = No Ability, 2 = Below Average Ability, 3 = Average Ability, 4 = Above Average
Ability, 5 = Exceptional Ability
Summated mean and standard deviation for each agricultural mechanics laboratory
management construct, based on the self-perceived abilities of secondary agriculture teachers,
are reported in Table 7. These summated means are proposed as multi-state benchmarks for
agricultural mechanics laboratory management competencies. Based on the responses of 503
secondary agriculture teachers, in six states, teachers should have at least an above average
ability to perform each agricultural mechanics laboratory management competency.
Table 7
Construct Benchmark Scores for Agriculture Teachers’ Ability to Perform Competencies
Construct
M
SD
Student Behavior Management
3.95
0.80
Personal Protection Equipment Management
3.91
0.68
Laboratory Activity Preparation
3.90
0.77
Hazardous Material Management
3.80
0.71
Laboratory Equipment Maintenance
3.65
0.73
Laboratory Facility and Program Management
3.55
0.64
Curriculum and Lesson Development
3.38
0.67
Program Public Relations and Recruitment
3.23
0.69
Note: 1 = No Ability, 2 = Below Average Ability, 3 = Average Ability, 4 = Above Average
Ability, 5 = Exceptional Ability
Objective 3
The purpose of Objective 3 was to use the construct outcomes of the factor-analytic and
psychometric analyses included in Objective 1 to determine if the self-perceived agricultural
mechanics laboratory management abilities of secondary agriculture teachers differed by teacher
career stage. Testing if teacher career stage (Huberman, 1989) had an effect on the self-perceived
ability of the 503 secondary agriculture teachers to perform agricultural mechanics laboratory
management competencies was important, because if a significant effect existed, the revised
competencies and constructs from this study could not be used to assess teachers in each career
stages.
April 20-23, 2011
Hence, construct scores, based on secondary agriculture teachers’ perceived ability to
perform each competency, served as the dependent variables; teacher career stage served as the
independent variable. The alpha level was set a priori at .05. The result of the MANOVA was
interpreted using Wilks’ lambda (Λ). There was not a significant effect of teacher career stage on
the dependent variables, the constructs identified in Objective 1, Λ = .91, F(32, 1683.24) = 1.34,
p = .10, ηp2 = .02. Additionally, the observed power (1 - β = .965) met the minimum power cutoff of 0.80, meaning that significant differences did not exist due to chance or error. Therefore,
the revised 33 competencies, in eight constructs, are appropriate for future assessments of
secondary agriculture teachers to perform agricultural mechanics laboratory management
competencies, for all five teacher career stages.
Conclusions, Implications, & Recommendations
As a result of this study, the 70 agricultural mechanics laboratory management
competencies included in the instrument modified by Saucier et al. were reduced to 33
competencies, in eight constructs, through factor-analytic procedures. A further outcome was
reflected in the psychometric evaluation of the newly identified eight agricultural mechanics
laboratory management constructs, which resulted in acceptable internal consistency reliabilities,
as measured by Cronbach’s alpha coefficients greater than .80 (Field, 2009).
Prior to this study, a benchmark for agricultural mechanics laboratory management
abilities of secondary agriculture teachers was not obvious in the literature. Although it is
important to acknowledge that the benchmarks proposed in this study are not normative data, the
benchmarks serve as a point of reference for future needs assessments of secondary agriculture
teachers’ ability to perform agricultural mechanics laboratory management competencies.
Because the 33 competencies, in eight constructs, were appropriate to assess agricultural
mechanics laboratory management competencies across all five teacher career stages, those
competencies and benchmarks provide an updated, succinct, and accurate measure for assessing
secondary agriculture teachers’ professional development needs related to agricultural mechanics
laboratory management.
Because beliefs of teachers are developed in part to the level of preparation regarding the
content (Thompson & Balschweid, 1999), comfort level with the content, (Knobloch & Ball,
2003), perceived value of the content (Lawrenz, 1985), past experiences with the content area
(Calderhead, 1996; Thompson & Balschweid), teacher education programs and entities
responsible for revising National Council for Accreditation of Teacher Education (NCATE)
standards should ensure that pre-service teachers are receiving adequate education and exposure
to the areas of agricultural mechanics laboratory management identified in this study. Although
adding or replacing coursework in teacher preparation programs may be difficult at many
institutions, teacher educators can engrain the concept of self-directed learning (Knowles, Holton
III, & Swanson, 2005) in their students, so that when needs are identified, teachers understand
that it is their obligation to remediate or expand their knowledge and abilities.
The National Research Agenda of Agricultural Education and Communication (Osborne,
n.d.), RPA 4, indicated the need to identify the professional development needs of agricultural
educators. The 33 competencies, in eight constructs, identified in this study are a valid and
April 20-23, 2011
reliable means to assess secondary agriculture teachers professional development needs related
to agricultural mechanics laboratory management. Furthermore, the benchmarks proposed in this
study can serve as a comparison for future needs assessments that include the 33 items identified
in this study. Therefore, state agencies or associations responsible for conducting assessments of
secondary agriculture teachers’ ability to perform agricultural mechanics laboratory management
competencies should use the competencies and benchmarks proposed in this study to assess the
secondary agriculture teachers ability to perform agricultural mechanics laboratory management
competencies in their states.
To further address the professional development needs of secondary agriculture teachers,
competency-based needs assessments should be developed for other areas of agricultural
mechanics, such as technical competencies, and program planning, development, and evaluation
(Garton & Chung, 1997). Also, methods of evaluating professional development needs should
extend beyond common measures of self-perceived competency. Researchers should consider
other avenues of assessing teacher competency, such as authentic assessment or performancebased assessment, much like those used in industry. Although the focus of this study was
confined to laboratory management competencies related to agricultural mechanics, the need for
safe and effective laboratory instruction and management spans far beyond the scope of
agricultural mechanics—and perhaps agricultural education—to include other core-academic and
career and technology education pathways.
April 20-23, 2011
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April 20-23, 2011
Agricultural Education Pre-Service Teachers’ Self-Perceived Abilities
to Teach Agricultural Mechanics
Brian L. Leiby
Agriscience Teacher, Marionville, Missouri
J. Shane Robinson
Assistant Professor, Oklahoma State University
James P. Key
Professor, Oklahoma State University
James G. Leising
Professor, University of Minnesota
Abstract
This study sought to assess the welding skills standards of pre-service teachers in agricultural
education during the fall 2009 school year at Oklahoma State University (N = 58). It was
concluded that the MCAG 3222 – Metals and Welding course had a positive impact on students’
perceived levels of competence to perform necessary welding tasks. MCAG 3222 – Metals and
Welding course be modified to focus more on “shielded gas selection and usage,” “welding
equipment settings, such as wire speed, temperature and polarity,” “safety rules for handling
oxy-acetylene welding gasses, and equipment,” “orange peel cutting of mild steel pipe, using a
plasma cutter or oxy-fuel torch,” and “electrode identification and selection.” These six skills
should be a priority of the course due to their top ten ranking prior to and at the end of instruction
based upon students’ MWDS.
Introduction
The viability of agricultural mechanics at the secondary level depends on agricultural education
teachers mastering the technical competencies needed to teach it effectively (Burris, Robinson, &
Terry Jr., 2005). In Oklahoma, welding skills have been developed by the Oklahoma Department
of Career and Technical Education (ODCTE, 2006). These skills pertain to the welding industry,
specifically and to the national welding industry, generally. Additionally, these Oklahoma
welding skills standards have been aligned with and endorsed by the American Welding Society
(AWS).
Skills standards provide a listing of necessary skills in which secondary students should be
competent. To ensure that competencies are met, written assessments are used to evaluate
student performance (ODCTE, 2006). Skills standards provide educators with a roadmap of
essential skills that they should teach. Skills standards also provide students with a list of
necessary skills which they should possess or acquire. Specifically, “Skills standards are aligned
with national skills standards; therefore, a student trained to the skills standards possesses
technical skills that make him/her employable in both state and national job markets” (ODCTE,
2006, p. A).
1
April 20-23, 2011
Studies have been conducted to assess teachers’ and students’ needs related to agricultural
mechanics. Johnson, Schumacher, and Stewart (1990) assessed the in-service needs of practicing
secondary agricultural educators in Missouri. They found that Missouri teachers had specific
needs related to managing the agricultural mechanics laboratory. In particular, all five
competencies receiving the highest MWDS (i.e., greatest deficiencies) were related to laboratory
safety (Johnson et al., 1990).
Burris et al. (2005) sought to determine the perceptions of university faculty in teacher
preparation programs across the country regarding the skills needed by pre-service students in
agricultural mechanics. They discovered that university faculty rated their students as “prepared”
in the selection and use of hand tools, “somewhat prepared” in the areas of agricultural power,
metal fabrication, electricity, building/construction, project planning and material selection,
concrete, and plumbing, and “poorly prepared” in handling machinery and equipment.
Saucier, McKim, Murphy, and Terry Jr., (2010) sought to determine the needs of 98 student
teachers in Texas regarding the management of the agricultural mechanics laboratory. They
concluded that there was a need for additional instruction in the areas of “lab equipment
diagnosis and repair, first aid, and safe disposal of hazardous materials” (p. 1). The authors
recommended that teacher educators continue to provide ongoing and professional development
opportunities for teacher improvement in agricultural laboratory management through
workshops, conferences, and structured coursework.
Saucier, Terry, Jr., and Schumacher (2009) found that agricultural mechanics instructors in
Missouri possessed the greatest areas of need in maintaining laboratory safety for students,
dealing with hazardous materials, and repairing equipment. McKim, Saucier, and Reynolds
(2010) found that secondary agricultural education teachers in Wyoming had the greatest needs
in the areas of “first aid, correcting hazardous laboratory conditions, and general laboratory
safety” (p. 129).
Increasing students’ technical competencies in agricultural mechanics is an escalating imperative
especially since most universities across the country are reducing their graduation requirements
below 128 hours (Burris et al., 2005). At Oklahoma State University, a two-credit hour course,
MCAG 3222 – Metals and Welding, is designed to increase pre-service teachers’ knowledge and
competencies in agricultural mechanics. However, little is known about the impact that a course
such as this one has on students’ competencies in agricultural mechanics over the duration of a
semester. This study is important because increasing pre-service teachers’ competencies in
agricultural mechanics, with special emphasis on welding, will improve their confidence (i.e.,
self-efficacy) to teach those skills once they become full-time instructors.
Self-efficacy refers to an individual’s beliefs about his or her abilities to accomplish tasks
(Bandura, 1997). Thoughts of self-efficacy regulate numerous functions of people’s lives,
including feelings, motivations, and courses of action (Bandura, 1994). “If people believe they
have no power to produce results, they will not attempt to make things happen” (Bandura, 1997,
p. 3). Inversely, individuals are more apt to achieve success when they believe they possess the
appropriate skills and support needed. Positive achievement assists individuals in building strong
feelings of self-efficacy (Bandura, 1994).
2
April 20-23, 2011
Bandura (1994) noted four sources which play important roles for the development of selfefficacy. These four sources consist of mastery experiences, vicarious experiences, social
persuasion, and physiological and emotional states (Bandura, 1994). Mastery experiences are the
most effective way of creating a strong sense of efficacy (Bandura, 1994). Mastery experiences
improve an individual’s self-efficacy beliefs. Inversely, individuals who fail to achieve often
experience slow or halted efficacy growth (Bandura, 1994). Vicarious experiences allow
individuals to gain confidence by observing others perform a given task. Social persuasion
assumes that individuals who have doubts concerning personal abilities are more likely to persist
if they are reinforced verbally (Schunk, 1989). Physiological and emotional state takes into
account influential efficacy factors such as mood, fatigue, stress, or the lack of stress, and how
these factors play a role in influencing an individual’s efficacy (Bandura, 1994).
These four sources have obvious implications for teachers (i.e., teacher self-efficacy). “Teacher
efficacy is the teacher’s belief in his or her capability to organize and execute courses of action
required to successfully accomplish a specific teaching task in a particular context” (TschannenMoran, Woolfolk, Hoy, & Hoy, 1998, p. 233). Bandura (1977) identified teacher efficacy as a
form of self-efficacy by which teachers construct internal beliefs of their ability to perform
teaching tasks at a proficient level. These internal beliefs have the potential to influence teachers’
level of expended effort related to persistence in difficult situations, resiliency in the face of
failures, and stress or depression (Bandura, 1997). Because an individual’s internal beliefs can
influence his or her performance, it is vital to understand teachers’ levels of self-efficacy
regarding agricultural mechanics.
Identifying the needs of pre-service teachers in agricultural mechanics is an important endeavor
due to a paucity of research in this area. Saucier et al. (2010) recommended that,
Future research within the realm of agricultural mechanics education should be explored
by researchers. In fact, little research has been conducted in this area of instruction over
the past 20 years. Agricultural mechanics courses still remain a popular option for many
secondary students and thus, require highly qualified agricultural educators who are
technically and pedagogically competent. (p. 13)
So, what are the technical skills and competencies of pre-service teachers in the area of
agricultural mechanics? Specifically, what welding skills do pre-service teachers find most
important to their future jobs as educators? Likewise, what are the skills in which pre-service
teachers are most competent at performing?
Purpose of the Study
The purpose of this study was to assess the welding skills standards of pre-service teachers in
agricultural education during the fall 2009 school year at Oklahoma State University (N = 58).
The study sought to assess pre-service teachers’ perceptions regarding the importance of
identified welding skills and their self-perceived level of competence to teach those skills as a
result of being enrolled in MCAG 3222 – Metals and Welding. The following objectives guided
the study.
1. Determine the perceived importance of teaching selected welding skills standards
according to pre-service teachers in agricultural education prior to and at the end of the
semester.
3
April 20-23, 2011
2. Determine the perceived competence to teach selected welding skills standards according
to pre-service teachers in agricultural education prior to and at the end of the semester.
3. Determine the need of pre-service curriculum enhancement in welding based on
perceptions (prior to and at the end of instruction) of pre-service agricultural education
teachers, using the Borich needs assessment model.
Methodology
The research design for this study was descriptive in nature (i.e., means and standard deviations).
However, in addition to basic descriptive statistics, the Borich Needs Assessment Model (1980)
was used to examine the discrepancies that existed between teachers’ perceived importance to
teach selected welding skills standards and their competence to teach selected welding skills
standards as a result of enrolling in MCAG 3222 – Metals and Welding. At Oklahoma State
University, pre-service teachers in agricultural education are required to take five hours of
mechanized agriculture. MCAG 3222 is considered two of the five hours required. Specifically,
MCAG 3222 – Metals and Welding is offered in the spring semester and is a teacher certification
requirement. Therefore, all teacher aspirants in agricultural education must pass the course
successfully by earning a grade of “C” or better. Typically, students enroll in MCAG 3222 –
Metals and Welding the spring semester of their junior year after taking the foundations course
in agricultural education and before entering their student teaching internship.
To determine the impact the MCAG 3222 – Metals and Welding course had on pre-service
teachers’ competencies, assessments were conducted prior to and at the end of instruction.
Specifically, assessments were conducted in August (during the second week of the semester)
and April (the week prior to the final examination).
The Borich Needs Assessment Model (1980) is a well documented tool that has been useful in
determining the in-service needs of practicing teachers (Garton & Chung, 1996; Johnson,
Schumacher, & Stewart, 1990; Newman & Johnson, 1994; Saucier et al., 2009) and highlighting
areas in need of curricular enhancement (Robinson, Garton, & Vaughn, 2007). Specifically, the
Borich Needs Assessment Model relies on the comparison of Mean Weighted Discrepancy
Scores (MWDS) (Borich, 1980). MWDS are deficiencies between the importance and
competence constructs that are determined through a three-step process that begins with
calculating a discrepancy score (DS). Discrepancy scores are determined by subtracting the
difference between a teachers’ surveyed response for their perceived importance to teach a given
skills standard from their perceived level of competence to teach the same skills standard. After a
DS is determined for every teacher on each skills standard, it is multiplied by the importance
rating for the given skills standard, resulting in a Weighted Discrepancy Score (WDS). WDSs
are then averaged to create a Mean Weighted Discrepancy Score (MWDS). For evaluation
purposes, the MWDSs are listed in numerical order from highest to lowest. Skills standards with
larger MWDS are in greater need of in-service/continued training by the pre-service teacher
(Garton & Chung, 1996) and curriculum development (Robinson et al., 2007).
The instrument used for this study consisted of determining the importance and competence
levels of pre-service teachers based on the 26 welding skills standards required of agriculture
teachers in Oklahoma (ODCTE, 2006). The 26 welding skills standards encompassed seven
constructs regarding welding (Table 1). The instrument employed a summated rating scale,
which ranged from 1 = No Importance or Competence, 2 = Below Average Importance or
Competence, 3 = Average Importance or Competence, 4 = Above Average Importance or
4
April 20-23, 2011
Competence, and 5 = High Importance or Competence. Face and content validity was established
by a panel of experts in agricultural education and agricultural biosystems engineering.
Reliability was assessed through two pilot tests. The initial test was used to gather data on how
the instrument performed. A small group of five pre-service agricultural education teachers was
used to assess the reliability of the instrument. These individuals made footnotes on the
instrument in order to mark the sections which were unclear, ambiguous, or confusing.
Modifications to the instrument were made based upon these teachers’ initial suggestions.
A second pilot test occurred in a special summer section of MCAG 3222 – Metals and Welding
(Summer 2009). The second administration of the pilot test was larger in nature with a
population of 23 participants. The second assessment was deemed necessary to increase
instrumental reliability due to the relatively limited sample size which occurred for the initial
assessment. Upon calculating the reliability estimates, all seven constructs met Nunally’s (1980)
requirement of .70 or higher with the exception of welding safety importance, which was
calculated at .54 (Table 1). Special caution should be taken when considering the items
representing the welding safety construct. However, “writ large,” section one of the instrument
was deemed reliable and suitable for use for formal data collection.
Table 1
Reliability Estimates of the Seven Welding Constructs
Constructs
Welding Safety
Welding Process & Procedure
Welding Knowledge
Oxy-Fuel
Brazing
Manual Arc Welding
Manual Cutting
Importance
Competence
.54
.73
.86
.79
.88
.91
.84
.79
.87
.94
.89
.89
.95
.94
Findings
Objective one sought to determine the perceived importance of teaching selected welding skills
standards according to pre-service teachers in agricultural education prior to and at the end of the
semester. It was found that all 26 skills standards were rated between “above average
importance” and “high importance” by pre-service teachers. Specifically, pre-service teachers in
agricultural education experienced positive growth regarding the importance of 22 skills
standards and a decline regarding the importance of four skills standards (Table 2).
The skills standards least important to pre-service teachers prior to instruction were “orange peel
cutting of mild steel pipe, using a plasma cutter or oxy-fuel torch” (M = 4.05, SD = 1.03),
“lighting, flame adjustment, and shut-down procedures of oxy-fuel welding equipment” (M =
4.10, SD = .96), and “slag chipping (weld cleaning)” (M = 4.12, SD = 1.02). In contrast, the skills
standards most important to pre-service teachers at the end of instruction comprised the welding
safety construct and consisted of “appropriate eyewear selection for welding” (M = 4.86, SD =
5
April 20-23, 2011
.35), “selection of personal protective equipment (PPE) for welding” (M = 4.86, SD = .35), and
“selection and use of fire extinguishers” (M = 4.81, SD = .45) (Table 2).
Table 2
Pre-service Teachers’ Perceptions of the Importance to Teach Selected Welding Skills Standard
Prior to and at the End-of-Instruction
Prior to
End of
Instruction
Instruction
Mean
Skills
M
SD
M
SD
Differences
1.
2.
3.
4.
5.
6.
7.
8.
9.
Slag chipping (weld
cleaning)
Lighting, flame
adjustment, and shutdown procedures of
oxy-fuel welding
equipment
Square groove butt joint
welding, using shield
metal arc welding in
the flat position
Joint preparation for
welding
T-joint fillet welding,
using shield metal arc
welding in the flat
and vertical up
position
Orange peel cutting of
mild steel pipe, using
a plasma cutter or
oxy-fuel torch
Selection of personal
protective equipment
(PPE) for welding
Identification of welding
errors, such as
improper travel speed
and excessive arc
length
Manual operation of a
plasma cutter
4.12
1.02
4.57
.55
+0.45
4.10
.96
4.51
.68
+0.41
4.12
.99
4.51
.55
+0.39
4.31
.68
4.60
.59
+0.29
4.19
.89
4.48
.63
+0.29
4.05
1.03
4.33
.72
+0.28
4.64
.79
4.86
.35
+0.22
4.36
.79
4.57
.59
+0.21
4.26
.94
4.45
.74
+0.19
6
April 20-23, 2011
Table 2 (Continued)
Skills
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
Organization and
maintenance of a
clean and safe work
area
Identification of major
parts of gas metal arc
welding (MIG)
equipment
Electrode identification
and selection
Advantages of the gas
metal arc welding
(MIG) method
Shielding gas selection
and usage
Cutting shapes in mild
steel plate, using a
plasma cutter
Advantages and
disadvantages of
brazing
Proper surface preparation
for brazing
Cutting mild steel plate at
a 90 degree angle,
using an oxy-fuel
torch
Selection and use of fire
extinguishers
Welding equipment
settings, such as wire
speed, temperature
and polarity
The purpose of using flux
in brazing
Weld testing for strength
and defects
Appropriate eyewear
selection for welding
Prior to
Instruction
End of
Instruction
M
SD
M
SD
Mean
Differences
4.48
.74
4.64
.53
+0.16
4.38
.79
4.52
.67
+0.14
4.37
.77
4.50
.55
+0.13
4.31
.78
4.44
.71
+0.13
4.51
.64
4.63
.54
+0.12
4.29
.86
4.41
.67
+0.12
4.14
.95
4.26
.83
+0.12
4.69
.52
4.79
.47
+0.10
4.31
.87
4.40
.66
+0.09
4.79
.61
4.81
.45
+0.02
4.64
.48
4.71
.51
+0.07
4.26
.94
4.33
.75
+0.07
4.45
.74
4.50
.63
+0.05
4.88
.40
4.86
.35
-0.02
7
April 20-23, 2011
Table 2 (Continued)
Skills
24. Safety rules for handling
oxy-acetylene
welding gasses, and
equipment
25. Cutting a hole in mild
steel plate, using an
oxy-fuel torch
26. Proper setup of equipment
for oxy-acetylene
cutting
Prior to
Instruction
End of
Instruction
M
SD
M
SD
Mean
Differences
4.69
.68
4.66
.53
-0.03
4.40
.77
4.34
.73
-0.06
4.71
.55
4.64
.53
-0.07
Note. Scale: 1 = No Importance, 2 = Below Average Importance, 3 = Average Importance, 4 =
Above Average Importance, 5 = High Importance
The top five skills standards in which pre-service teachers experienced the greatest amount of
perceived increase regarding importance prior to and at the end of instruction was “slag chipping
(weld cleaning)” (+0.45), “lighting, flame adjustment, and shut-down procedures of oxy-fuel
welding equipment” (+0.41), “square groove butt joint welding using shield metal arc welding in
the flat position” (+0.39), “joint preparation for welding” (+0.29), and “t-joint fillet welding,
using shield metal arc welding in the flat and vertical up position” (+0.29). In contrast, preservice teachers experienced a decline in perceived importance on four skills standards. These
standards consisted of “appropriate eyewear selection for welding” (-0.02), “safety rules for
handling oxy-acetylene welding gasses, and equipment” (-0.03), “cutting a hole in mild steel
plate, using an oxy-fuel torch” (-0.06), and “proper setup of equipment for oxy-acetylene
cutting” (-0.07) (Table 2).
Objective two sought to determine the perceived competence to teach selected welding skills
standards according to pre-service teachers in agricultural education prior to and at the end of the
semester. It was found that the 26 skills standards ranged between “below average competence”
and “above average competence” by pre-service teachers prior to instruction (Table 3). However,
at the end of instruction, pre-service teachers rated themselves between “average competence”
and “high competence” regarding their ability to teach the same 26 skills standards. Specifically,
pre-service teachers experienced a positive perceived increase in competence on all 26 skills
standards from the beginning of the semester to the end (Table 3).
Prior to instruction, pre-service teachers were least competent in their ability to teach skills
standards related to “lighting flame adjustment and shut-down procedures of oxy-fuel welding
equipment” (M = 2.21, SD = 1.09), “advantages and disadvantages of brazing” (M = 2.31, SD =
1.22), and “orange peel cutting of mild steel pipe, using a plasma cutter or oxy-fuel torch” (M =
2.31, SD = 1.22) (Table 3). In contrast, at the end of instruction, pre-service teachers were most
8
April 20-23, 2011
competent at teaching skills standards related to “appropriate eyewear selection for welding” (M
= 4.81, SD = .40), “selection of personal protective equipment (PPE) for welding” (M = 4.62, SD
= .62), and “organization and maintenance of a clean and safe work area” (M = 4.60, SD = .66).
Table 3
Pre-service Teachers’ Competence to Teach Selected Welding Skills Standards Prior to and at
the End of Instruction
Prior to
End of
Instruction
Instruction
Mean
Skills
M
SD
M
SD
Differences
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Lighting flame adjustment
and shut-down
procedures of oxy-fuel
welding equipment
The purpose of using flux
in brazing
Advantages and
disadvantages of
brazing
Proper setup of equipment
for oxy-acetylene
cutting
Square groove butt joint
welding, using shield
metal arc welding in
the flat position
T-joint fillet welding, using
shield metal arc
welding in the flat and
vertical up position
Proper surface preparation
for brazing
Electrode identification
and selection
Cutting mild steel plate at a
90 degree angle, using
an oxy-fuel torch
Manual operation of a
plasma cutter
Orange peel cutting of mild
steel pipe, using a
plasma cutter or oxyfuel torch
2.21
1.09
4.50
.83
+2.29
2.40
1.19
4.21
.75
+1.81
2.31
1.22
4.02
.87
+1.71
2.93
1.42
4.48
.86
+1.55
2.60
1.27
4.12
.86
+1.52
2.64
1.28
4.07
.87
+1.43
2.98
1.37
4.40
.77
+1.42
2.63
1.28
4.00
.70
+1.37
2.71
1.45
4.05
.96
+1.34
2.88
1.42
4.12
.83
+1.24
2.31
1.22
3.55
1.04
+1.24
9
April 20-23, 2011
Table 3 (Continued)
Skills
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
Joint preparation for
welding
Safety rules for handling
oxy-acetylene welding
gasses, and equipment
Shielding gas selection and
usage
Identification of major
parts of gas metal arc
welding (MIG)
equipment
Cutting shapes in mild
steel plate, using a
plasma cutter
Identification of welding
errors, such as
improper travel speed
and excessive arc
length
Slag chipping (weld
cleaning)
Weld testing for strength
and defects
Cutting a hole in mild steel
plate, using an oxyfuel torch
Advantages of the gas
metal arc welding
(MIG) method
Welding equipment
settings, such as wire
speed, temperature
and polarity
Selection of personal
protective equipment
(PPE) for welding
Appropriate eyewear
selection for welding
Prior to
Instruction
End of
Instruction
M
SD
M
SD
Mean
Differences
2.98
1.26
4.21
.78
+1.23
3.02
1.42
4.14
.87
+1.22
2.55
1.15
3.76
.92
+1.21
2.79
1.24
3.98
.84
+1.19
2.74
1.34
3.93
.92
+1.19
2.86
1.30
3.98
.87
+1.12
3.50
1.33
4.57
.70
+1.07
2.88
1.15
3.90
.93
+1.02
2.98
1.41
3.90
1.05
+0.92
3.14
1.37
4.02
.85
+0.88
2.88
1.25
3.76
.91
+0.88
3.88
1.04
4.62
.62
+0.74
4.14
1.03
4.81
.40
+0.67
10
April 20-23, 2011
Table 3 (Continued)
Skills
25.
26.
Organization and
maintenance of a clean
and safe work area
Selection and use of fire
extinguishers
Prior to
Instruction
End of
Instruction
M
SD
M
SD
Mean
Differences
4.12
.90
4.60
.66
+0.48
3.69
1.14
4.14
.87
+0.45
Note. Scale: 1 = No Competence, 2 = Below Average Competence, 3 = Average Competence, 4
= Above Average Competence, 5 = High Competence
The top five skills standards in which pre-service teachers experienced the greatest amount of
perceived growth prior to and at the end of instruction was “lighting flame adjustment and shutdown procedures of oxy-fuel welding equipment” (+2.29), “the purpose of using flux in brazing”
(+1.81), “advantages and disadvantages of brazing” (+1.71), “proper setup of equipment for oxyacetylene cutting proper surface preparation for brazing” (+1.55), and “square groove butt joint
welding, using shield metal arc welding in the flat position” (+1.52). In all, pre-service teachers
in agricultural education perceived in excess of a one-point growth on 14 of the 26 skills
standards (Table 3).
Students showed the least amount of growth in “advantages of the gas metal arc welding (MIG)
method” (+0.88), “welding equipment settings, such as wire speed, temperature, and polarity”
(+0.88), “selection of personal protective equipment (PPE) for welding” (+0.74), “appropriate
eyewear selection for welding” (+0.67), “organization and maintenance of a clean and safe work
area” (+0.48), and “selection and use of fire extinguishers” (+0.45) (Table 3).
Objective three sought to determine the need of pre-service curriculum enhancement in welding,
based on perceptions (prior to and at the end of instruction) of pre-service agricultural education
teachers, using the Borich needs assessment model. Five skills standards were consistently in the
top ten in terms of MWDS prior to and at the end of instruction. These five standards consisted
of “shielded gas selection and usage” (Rank = 1prior to instruction, MWDS = 8.32; Rank = 2end of
instruction, MWDS = 3.75), “welding equipment settings, such as wire speed, temperature and
polarity” (Rank = 4prior to instruction, MWDS = 7.96; Rank = 1end of instruction, MWDS = 4.26), “safety
rules for handling oxy-acetylene welding gasses, and equipment” (Rank = 5prior to instruction, MWDS
= 7.83; Rank = 9end of instruction, MWDS = 1.79), “orange peel cutting of mild steel pipe, using a
plasma cutter or oxy-fuel torch” (Rank = 9 prior to instruction, MWDS = 7.30; Rank = 3end of instruction,
MWDS = 3.26), and “electrode identification and selection” (Rank = 9prior to instruction, MWDS =
7.30; Rank = 8end of instruction, MWDS = 2.19).
Conclusions
It was concluded that the MCAG 3222 – Metals and Welding course had a positive impact on
students’ perceived levels of competence to perform necessary welding tasks. Overall, when
11
April 20-23, 2011
using a 5–point summated scale, students ranged from almost a one-half point gain to in excess
of a two point gain regarding their competence at teaching the 26 skills standards as a result of
completing the MCAG 3222 – Metals and Welding course. This finding supports the position
that self-efficacy can be enhanced when people are provided meaningful experiences and the
time needed to practice and master a given task (Bandura, 1997).
Prior to enrolling in MCAG 3222 – Metals and Welding, pre-service teachers were least
competent in their ability to perform the skills standards related to welding process and
procedure (i.e., lighting an oxy-acetylene torch and cutting mild steel). However, at the end of
the semester, pre-service teachers remained most competent at performing welding safety (i.e.,
selecting appropriate eyewear and PPE). This finding contradicts numerous research studies
regarding the professional development needs of current agricultural education teachers in the
area of safety (McKim et al., 2010; Rosencrans & Martin, 1997; Saucier et al., 2010; Saucier et
al., 2009).
Pre-service teachers perceived the welding safety construct to be the most important skill
standard at the end of instruction. This conclusion supports a previous finding by Slusher (2009)
who found that general farm safety was a highly sought after competency of agricultural industry
experts when employing high school graduates in the animal science industry. Further, preservice teachers rated all 26 welding skills standards “above average” in importance, which
exceeds the conclusion drawn by McKim et al. (2010) who noted that “nearly all of the
competencies [of Wyoming agriculture teachers] were determined to be at least of average
importance, nearly half of which were perceived as being of above average importance” (p. 140).
Overall importance means from beginning to end of instruction assessments showed an increase
of +.15 points on a 5-point scale. Although this increase is not as steep as the perceived change
in competence, it should be noted that importance ratings were higher than confidence ratings for
all skills standards prior to instruction. So, there was not as much room for growth in this area.
Further, it should be noted that the importance ratings were higher than confidence ratings on
each of the welding skills standards throughout the duration of the course. This finding aligns
with previous research by Radhakrishna and Bruening (1994) and Robinson, Garton, and
Vaughn (2007) who found that graduates tend to rate items more important than they do their
ability to perform them.
Overall, five skills standards were identified as being in need of curricular enhancement based
upon their MWDS prior to and at the end of the semester. These five were “shielded gas
selection and usage,” “welding equipment settings, such as wire speed, temperature and
polarity,” “safety rules for handling oxy-acetylene welding gasses, and equipment,” “orange peel
cutting of mild steel pipe, using a plasma cutter or oxy-fuel torch,” and “electrode identification
and selection.”
Implications
The findings of this study raise a few questions. Although encouraging, why do these pre-service
teachers appear to have the greatest competence for performing skills related to welding safety?
Could it be these students struggle to self-regulate? Perhaps they are overly confident in their
ability to practice safety while welding. Knobloch and Whittington (2003) found that student
12
April 20-23, 2011
teachers can be overly confident in their abilities to perform certain skills related to teaching. So,
perhaps these students are similar to the student teachers in Knobloch’s and Whittington’s study
in age and maturity level, and they too were overly confident in their abilities. Also, maybe these
pre-service teachers come from secondary programs where safety was emphasized. Regardless,
this finding is unique and encouraging so long as it depicts teachers’ feelings accurately.
It could be implied that these students were able to achieve mastery experiences (Bandura, 1994)
on these welding skills standards throughout the duration of the course, which enabled them to
feel more confident at performing all welding skills standards. As such, these teachers should be
more confident at teaching these skills standards to their future students because efficacy leads to
successful teaching (Tschannen-Moran et al., 1998).
Recommendations for Practice
It is recommended that the MCAG 3222 – Metals and Welding course be modified to focus more
on “shielded gas selection and usage,” “proper setup of equipment for oxy-acetylene cutting,”
“safely rules for handling oxy-acetylene welding gasses and equipment,” “orange peel cutting of
mild steel pipe using a plasma cutter or oxy-fuel torch,” “welding equipment, such as wire speed,
temperature and polarity,” and “electrode identification and selection.” These six skills should be
a priority of the course due to their top ten ranking prior to and at the end of instruction based
upon students’ MWDS. Also, because students rated all skills as “above average importance,”
then they all should be retained in the MCAG 3222 – Metals and Welding course. Special
attention should be paid to helping students “identify welding errors, such as improper travel
speed and excessive arc length,” as this skill went from being last in terms of a skill needed for
curriculum enhancement prior to instruction to the third most needed skill for curriculum
enhancement at the end of the semester. Finally, since the welding safety construct coefficient
was low, it is recommended that further research explore this phenomenon and make
improvements to the instrument where necessary.
Recommendations for Future Research
It is recommended that this study be replicated in other states. It is possible that the results would
be similar to the findings in this study. Yet, different states might be emphasizing skills other
than welding. For instance, with the prominence of the “green” energy (i.e., alternative energy)
phenomenon, it stands to reason that some teacher preparation programs might be introducing or
considering integrating alternative energy into their existing curriculums to serve students’ needs
in the 21st century better. Agricultural mechanics courses are a natural “fit” for teaching students
about alternative energy and the implications it has on agricultural education (blind authors,
2010). As such, it is important to determine what other bordering states are teaching their preservice teachers in agricultural mechanics. Also, future research should assess pre-service
teachers’ knowledge and self-efficacy to teach other agricultural mechanics content areas outside
of welding. For instance, what knowledge and level of self–efficacy do teachers possess in areas
such as concrete, plumbing, and electricity? Future studies should explore these phenomena.
13
April 20-23, 2011
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Research on motivation in education: Goals and cognitions, Volume 3, 13–44. San
Diego, CA: Academic.
Slusher, W. L. (2009) An assessment of the animal science technical skills secondary
agricultural education graduates need for employment in the animal science industry: A
Delphi Study. Unpublished thesis, Oklahoma State University, Stillwater, OK.
Tschannen-Moran, M., Woolfolk Hoy, A., & Hoy, W. K. (1998). Teacher efficacy: Its meaning
and measure. Review of Educational Research, 68(2), 202–248. doi:
10.3102/00346543068662202
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Aligning Extension Education Curriculum at Land Grant Universities with
Professional Competencies: A Delphi Study
Carl Igo, Montana State University
Abstract
This descriptive study utilized a Delphi methodology to explore the career preparation of
extension education students in the land grant university system through an analysis of current
curriculum and its alignment with professional extension work competencies as identified by
Harder, Place, and Scheer (2010). Academic professors in conjunction with Extension regional
or district department heads were utilized to explore the professional competencies as they
related to the preparedness of graduates and new hires, the hiring process, specific job skills,
and courses within extension education degree programs. Over 300 courses falling into 24
course categories at the undergraduate level and 18 at the graduate level were identified by
extension education professors at LGU‘s that matched the 19 professional competencies
presented. Extension administrators identified 65 different sub categories within the 19
competency areas outlining specific skills needed for successful careers in Extension. The
conclusions revealed that cooperation between Extension administrators and extension
education professors will result in improved programs so that both will thrive and grow with the
changing environment. Recommendations found need for further research in the areas of hiring
practices and self reflection by professionals in both groups to analyze their own programs and
practices.
Introduction & Conceptual Framework
Since its beginning in 1914 with the Smith-Lever Act, Cooperative Extension has been a
dynamic organization that seeks to meet the needs of an ever-changing society. It was this act
that created the Cooperative Extension Service (CES) at each land grant university. As one of the
three components of a land grant university (Outreach, Research, and Teaching), Extension
strives to achieve its mission of advancing knowledge for agriculture, the environment, human
health and well-being and communities. This mission is directly delivered by local county
extension agents who form the link between the land grant university and local community
through educational programming.
The ability of Extension to be successful relies on the professional abilities of extension agents to
interact with clientele (Stone & Coppernoll, 2004). One method for future agents to prepare for
successful careers in Extension is to enroll in an undergraduate or graduate degree program at a
college or university; however, minimal current research has been conducted on academic
preparation for careers in extension (Benge, Mashburn, & Harder, 2008). Historically, extension
education research has focused on topics more often associated with work responsibilities of an
extension agent, such as program planning and evaluation. These, along with media presentation
development, were found to be the most important instructional skills needed for success as an
extension agent in the past (Legacy & Wells, 1987). Acker and Grieshop (2004) examined the
types of undergraduate and graduate courses offered in the broader area of agricultural and
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April 20-23, 2011
extension education. Communication, personal and professional leadership, and teaching
methods were the most common topics at the undergraduate level, while graduate coursework
focused on research, advanced teaching methods, and leadership development. The concept of
identifying core competencies is not new to Extension. Several studies have been conducted from a
variety of different positions and perspectives. Beeman, Cheek, McGhee, and Grygotis (1979) first
assessed the importance of core competencies needed by extension agents in Florida as perceived by
both county agents and state staff. Betts, Firth, Watters, & Shepherd (1996) reported on core
competencies for Arizona county agents working with youth- and families-at-risk. Cooper and
Graham (2001) identified 57 competencies needed by county agents and county Extension
supervisors in Arkansas. These earlier studies have led to the development of several
competency models used in state Extension systems. Texas, Michigan, North Carolina and 4-H all
have their own competency models (Stone & Coppernoll, 2004; Michigan State University
Extension, 2008; North Carolina State University Cooperative Extension, nd.; & Stone &
Rennekamp, 2004). However, there is considerable variance in the existing models. Some models
have as few as 19 competencies outlined, while the 4-H model includes over 200 competencies. This
inconsistency makes it difficult to determine which competencies extension professionals really need
to be proficient in their jobs.
Scheer, Ferrari, Earnest, and Connors (2006) research on the review of extension education at
The Ohio State University was the first published article to focus exclusively on extension
education in recent years. Findings from this study revealed a conceptual model of competencies
for extension agents. Ten core competency areas were identified as necessary for success in
Cooperative Extension: (a) Extension knowledge, leadership, and management; (b) technology;
(c) communications; (d) program planning, implementation, and evaluation; (e) applied research;
(f) diversity and pluralism; (g) marketing and public relations; (h) theories of human
development and learning; (i) risk management; and (j) community development process and
diffusion. Benge, Mashburn, and Harder (2008) further explored the idea to describe the types of
extension education courses offered at the undergraduate and graduate levels according to the
Ohio State model. The study found that extension education curriculum most frequently included
courses related to Extension knowledge, leadership, and management; theories of human
development and learning; program planning, implementation, and evaluation; and applied
research (at the graduate level). In addition, nineteen land grant universities that offered
extension education as a major, minor or graduate specialization were identified. A follow-up
study conducted by Harder, Place, and Scheer (2010) explored the future competencies necessary
for entry-level Extension professionals in 2015. The study identified nineteen core competencies
needed for success. These competencies included: program planning, implementation and
evaluation; teaching skills; accountability; ability to utilize technology for program delivery;
self-management; problem-solving; oral and written communication skills; cultural sensitivity;
professionalism; relationship building; interpersonal skills; organizational and personal
leadership development; applied research skills; ability to attain extramural funding;
technical/subject matter area expertise; and volunteer development. The researchers
recommended that future research should use the competencies from the study as a framework
for examining the career preparedness of extension education graduates, competencies
commonly held by pre-entry Extension applicants, and competency levels of current Extension
employees.
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April 20-23, 2011
While the previous studies effectively identified professional competencies, further research was
needed to examine current extension education programs and their effectiveness in preparing
graduates for extension service work. Additional research was also needed to examine the
preparedness of graduates and new hires, explore the current curriculum as it relates to these
competencies, and describe what these competencies mean within the context of entry level
Extension positions to develop recommendations for curriculum and professional development
opportunities. Therefore, this research concentrated on describing the alignment of extension
education curriculum with the professional competencies needed to prepare students for
successful careers in cooperative extension. This study addressed the Agricultural Education in
Domestic and International Settings: Extension and Outreach of the National Research Agenda
Research Priority 2: Identify the needs and competencies of stakeholders and professional
practitioners in nonformal agricultural extension education.
The purpose of the study was to explore current collegiate extension education curriculum and
Extension professional competencies in order to improve the preparation of future extension
agents across the nation. Specifically, the study addressed the following objectives.
1. Describe how current extension education curriculum in undergraduate and graduate
programs of study at land grant universities aligned with the professional competencies
needed for a successful career in Extension.
2. Describe specific job skills related to professional competencies needed by entry-level
extension agents.
3. Compare perceptions of Extension administrators and professors concerning the
importance of professional competencies within hiring practices and level of career
preparedness.
4. Develop a professional framework model for Extension and extension education
programs at land grant universities.
Methods and Procedures
Methodology
A three-round, modified Delphi technique was utilized to conduct this study from October 2009
to February 2010. A traditional Delphi begins with an open ended question and subsequent
rounds seek to reach consensus on the findings from the first round (Dalkey & Helmer, 1963).
The methodology in this study was modified in order to ask different questions in rounds one and
two, yet still reach consensus by the third round. This technique was selected for its ability to
gather and refine the opinions of experts in order to obtain consensus about some aspect of the
present or the future (Fischer, 1978). In rounds one and two, questions were asked related to
competencies and their alignment with degree programs and on-the job skills, and the perceived
level of preparedness of graduates and new hires in the last five years. The goal of round three
was to reach a consensus among the experts related to extension education curriculum, hiring
practices, and professional development opportunities for entry-level extension professionals.
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April 20-23, 2011
Participant Selection
Selection of participants for a Delphi study is considered the most important step in the entire
process because it directly relates to the quality of the results generated (Judd, 1972; Taylor &
Judd, 1989; Jacobs, 1996). Although no exact criterion has been established for selecting
participants for a Delphi study, Hsu and Sandford (2007) offer the following recommendations:
(1) choose decision makers who will utilize the outcomes of the Delphi study; (2) select
professional staff members together with their support team; and (3) consider respondents whose
judgments are being sought. All these criteria were met in the participant selection for this study.
In this study, two separate panels of experts were created. One consisted of agricultural and
extension education professors at land grant universities (LGU„s) where 27 had minor and/or
major degree programs in extension education at the undergraduate or graduate level. The second
panel of experts consisted of regional department heads, district or area directors or the
equivalent position in each state (further referred to as Extension administration) who were
responsible for hiring and evaluating county agents in their state. In order to identify these
participants, an online search was conducted of all land grant university websites to find
extension education degree programs and was guided by the previous research conducted by
Benge, Mashburn, and Harder (2008). Follow-up phone calls were made to many of the
universities to verify the existence of a degree program in extension education. Cross referencing
with the American Association for Agricultural Education directory was also used to identify
appropriate faculty members. Once the list of land grant universities was established, a second
online search was conducted to identify the Extension administrators for each of the states
identified as having extension education degree programs. The pool consisted of 123 potential
experts. This included 37 extension education professors at land grant universities and 86
Extension administrators. Round one responses narrowed the panel to 15 professors and 29
extension administrators. The final response pool that completed the all three rounds of the
study was 15 professors and 23 administrators. Each of the participants was assigned an
identification number and names were not revealed in any part of the study. No demographic
information was collected. This allowed respondents to react and respond freely to the questions
posed in each round (Linstone & Turoff, 1975; Pollard & Pollard, 2004).
Data Analysis
Although the Delphi method is a respected technique for seeking consensus, there is no
commonly accepted definition of consensus in a Delphi study (Fink, Kosekcoff, Chassin, &
Brook, 1984). However, Williams and Webb (1994) stressed the importance of identifying
consensus criteria prior to data collection. For the purposes of this study, consensus was
established for an item when 80% of respondents indicated they either “Agree” or “Strongly
Agree” with the statements. This was based on Green‟s (1982) suggestion that at least 80% of
Delphi subjects need to rate three or higher on a four point Likert-type scale in order for
consensus to be reached. A conventional content analysis approach was used to code the first
round responses (Neuendorf, 2002). Data was read by multiple researchers, highlighted to derive
codes using the exact words that captured key thoughts and concepts, and then verified to
increase inter-rater reliability (Miles & Huberman, 1994; Morgan, 1993; Morse & Field, 1995).
The Statistical Package for Social Sciences (SPSS) version 17.0 software program was used to
calculate means and standard deviations for data from rounds two and three. An independent
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April 20-23, 2011
samples t-test was also used to verify significance of responses in round two reporting p values
for statistical significance (p<.05) and Cohen‟s d for effect size.
Findings
Twenty two different land grant universities were represented in the study from the states of
Arkansas, Colorado, Florida, Georgia, Indiana, Iowa, Kansas, Michigan, Minnesota, Montana,
Nebraska, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon,
Tennessee, Utah, Virginia, and West Virginia. Of the 15 extension education professors, five
were female (33.3 %) and 10 were male (66.7%). Of the 22 Extension administrators, five were
female (22.7%) and 17 were male (77.3%).
Objective One
The first objective of the study sought to describe how current extension education curriculum in
undergraduate and graduate programs of study at land grant universities aligned with the
professional competencies needed for a successful career in Extension. Overall, over 300 courses
falling into 24 course categories at the undergraduate level and 18 at the graduate level were
identified by extension education professors at LGU„s matched the 19 professional competencies
presented. Some programs, however, did not have specific courses that matched particular
competencies. There was a shortage of courses that taught the competencies of developing
extramural funding, applied research skills as well as volunteer management at the
undergraduate level. At the graduate level, there were few courses with regard to cultural
sensitivity, communications skills and volunteer development.
Objective Two
The second objective sought to describe specific job skills related to professional competencies
needed by entry-level extension agents. Extension administrators identified 65 different sub
categories within the 19 competency areas (Table 1). The only categories that did not reach
consensus in round three were online social networking as it related to ability to utilize
technology for program delivery; online social networking as it related to the competency of
relationship building; and general knowledge as being more important than being an expert in
one technical area.
Table 1
Skill categories and levels of agreement as indicated by extension administrators (n=23) in
round three
Competency
Ability to utilize
technology for
program delivery
Accountability
Associated Skills
Communication & General
Correspondence
Microsoft Office Programs
Equipment Setup
On-Line Web Delivery
Social Networking *
Written Documentation & Reporting
Impacts
Accountability in Relationships
Program Development & Evaluation
Tight Budgets Lead To Increased
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April 20-23, 2011
Mean
3.74
SD
0.44898
3.61
3.39
3.13
2.70*
3.87
0.49901
0.65638
0.54808
0.63495
0.34435
3.87
3.48
3.48
0.34435
0.51075
0.66535
Applied Research
Skills
Communication Skills
Cultural Sensitivity
Development of
Extramural Funding
Organizational
Leadership
Development
Personal Leadership
Development
Problem Solving
Professionalism
Program Evaluation
Program
Implementation
Expectations
Communicating Results
Articulate Research
Keeping Current in Research Based
Information
Conducting Research
Teaching & Presenting
Working & Communicating w/
Different People
Speaking Skills
Writing Skills
Respect For Different Perspectives
Consider Different Audiences
Understand Learning Styles of Different
Groups
Collaboration
Knowledge of Funding Sources
Decrease in Public Funding
Maintain High Visibility in The County
Working in a Team Environment
People Skills More Important than
Subject Matter
Develop Leaders to Take on Roles
Provide Program Leadership
Understand Components of Successful
Organizations
Desire for Lifelong Learning
Understand Own Leadership Style &
How to Improve Skills
Understand Leadership Styles of Others
& How to Work w/ Them
Provide Possible Solutions to Clients
Sound Decisions Aligned w/ Program
Goals
Build Strong Rapport
Demonstrate Credibility of the
Profession
Continue Professional Development
Measure, Document & Report Impacts
& Outcomes
Determining Accountability &
Maintaining Focus
Showing Changes Related to Material
Taught
Ability to Form Partnerships & Build
Coalitions
Take Ideas & Make Them Happen
Quality Programs that Fit Mission &
Make Difference
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April 20-23, 2011
3.61
3.39
3.26
0.49901
0.58303
0.61919
3.01
3.87
3.83
0.66831
0.34435
0.38755
3.74
3.70
3.70
3.48
3.43
0.44898
0.47047
0.47047
0.51075
0.50687
3.59
3.48
3.30
3.70
3.57
3.48
0.50324
0.59311
0.55880
0.55880
0.50687
0.51075
3.43
3.39
3.13
0.50687
0.49901
0.34435
3.43
3.43
0.50687
0.50687
3.26
0.44898
3.48
3.39
0.51075
0.49901
3.78
3.70
0.42174
0.47047
3.57
3.61
0.50687
0.49901
3.55
0.50965
3.50
0.51177
3.61
0.49901
3.61
3.43
0.49901
0.50687
Program Planning
Relationship Building
Self Management
Teaching Skills
Technical / Subject
Matter Expertise
Volunteer
Development
Needs Assessments
Planned Activities to Alter Behavior,
Attitude or Aspiration
Plan of Work w/ Efforts Justified
Utilize Clientele to Develop Program
Positive Relationships = Success /
Builds Rapport
Networking to Develop
Partnerships/Collaborations
Become Trusted Provider / Someone to
Rely On
Meet People at Community Functions
Online Social Networking *
Time Management
Self-Motivated / Disciplined / Directed /
Starter
Cater to Audience Needs
Utilize Variety of Techniques
Appeal to Multiple Learning Styles
Knowledge of Subject Matter
Appropriate to Position & Function
Lifelong Learner
Must be balanced w/ People &
Organizational Skills
General Knowledge *
How to Organize People
Important to Meet Needs w/ Reduced
Funds
Work w/ & Train Volunteers
3.52
3.48
0.51075
0.51075
3.30
3.17
3.59
0.47047
0.38755
0.50324
3.50
0.51177
3.48
0.51075
3.04
2.52*
3.95
3.91
0.47465
0.51075
0.21320
0.28810
3.70
3.61
3.57
3.52
3.48
3.48
3.30
0.47047
0.49901
0.50687
0.51075
0.50687
0.51075
0.47047
2.65*
3.39
3.35
0.57277*
0.49902
0.57277
3.35
0.57277
Note: *Starred items indicate categories that did not reach consensus; Likert scale: 4 = Strongly
Agree, 3 = Agree, 2 = Disagree, 1 = Strongly Disagree
Objective Three
The third objective sought to compare perceptions of the importance of professional
competencies within hiring practices and level of career preparedness between extension
professors and administrators (Table 2). Extension education professors ranked interpersonal
skills, technical subject matter expertise and relationship building as the competencies in which
graduates were most prepared. Competency areas that graduates were ranked lowest in were
accountability, volunteer development and developing extramural funding. Extension
administrators perceived that entry-level agents were the most prepared in their ability to utilize
technology for program delivery, technical subject matter expertise and communication skills.
The perceived weakest areas were development of extramural funding, program evaluation and
volunteer development. These findings indicate that there is some agreement among the two
groups that graduates are lacking in their preparation within the areas of volunteer development
and the development of extramural funding.
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April 20-23, 2011
Table 2
Comparison of perceptions of level of preparedness of graduates and entry-level extension
agents between professors and administrators (n=40)
PEt
p
Cohen’s
Competency
rank rank
d
Able to utilize technology for program
8
1
2.140
0.039* 0.51939
delivery
Accountability
17
10
1.367
0.180
0.49729
Applied Research Skills
14
15
-0.688
0.496
0.26522
Communication Skills
9
3
-0.172
0.865
0.05525
Cultural Sensitivity
16
7
1.295
0.203
0.44203
Develop Extramural Funding
19
17
1.879
0.068
0.75146
1
4
-3.501 0.001**
1.0056
13
16
-1.455
0.154
0.48624
Organizational Leadership
Development
Personal Leadership Development
4
12
-2.592
0.013* 0.76251
Problem Solving
10
6
-0.883
0.383
0.25417
Professionalism
7
8
-1.369
0.179
0.44203
Program Evaluation
15
18
-1.761
0.086
0.69620
Program Implementation
6
13
-2.592
0.013* 0.76251
Program Planning
5
14
-2.504
0.017* 0.89512
Relationship Building
3
11
-2.855
0.007* 0.82882
Self-management
12
5
-0.051
0.959
0.01105
Teaching Skills
11
9
-0.784
0.438
0.26522
Technical / Subject Matter Expertise
2
2
-2.028
0.050
0.61885
Volunteer Development
18
19
-1.308
0.199
0.47519
Note: *Starred items indicate areas that were found to be significantly different at p<.003**
When comparing the level of preparedness of graduates to the importance Extension
administrators place on each competency during the hiring process, there were differences in the
rankings of the competencies as well. Administrators ranked competencies found within the
concept of core interpersonal skills - communication skills, interpersonal skills, professionalism,
relationship building, accountability, self-management, and problem solving - to be the most
important during the hiring process. The competencies of volunteer development, development
of extramural funding, organizational leadership development, and applied research skills were
perceived as less important during the hiring process.
Starred items in Table 2 indicate areas found to be significantly different at p<.003 due to
adjustment for Type I error using the Bonferroni correction. Cohen‟s d value was also calculated
to measure effect size. Cohen (1988) recommended that effect size can be standardized by
measuring the mean difference in terms of standard deviation. Gravetter & Wallnau (2007)
indicate that a d value of 0.2 is a small effect size, 0.5 is a medium effect size while a d of 0.8 or
greater has a large effect size. In this study, those with large effect sizes were: interpersonal
skills (d=1.0056), program planning (d=0.89512), and relationship building (d=0.82882).
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April 20-23, 2011
Objective Four
The fourth objective sought to develop a framework for extension education programs at land
grant universities. Based on the results of the study, the following models (Figures 1 & 2) were
created revealing the current course categories being taught at the undergraduate and graduate
level and their alignment with the specific competencies necessary for Extension.
Figure 1. Aligning curriculum and competencies at the undergraduate level
Figure 2. Aligning curriculum and competencies at the graduate level
The models reveal there were some competencies that were addressed more heavily at the
graduate level such as applied research skills, and others more heavily at the undergraduate level
such as communication skills. The model also shows that there were some courses that address a
wide variety of necessary competencies (program planning / instructional development and
internship / field experience) while others were very targeted to specific competencies (diversity
& multicultural, writing, speaking, statistics & data analysis and computer applications).
Conclusions, Implications and Recommendations
Objective One
The first objective sought to describe how current extension education curriculum at land grant
universities aligned with the professional competencies. Professors reached consensus on 16
course categories at the undergraduate level and 17 course categories at the graduate level that
are currently being taught. It was evident that there are currently areas such as developing
extramural funding and volunteer development that extension education programs could improve
in order to effectively deliver necessary competencies. These findings were relatively consistent
with the study conducted by Benge, Mashburn & Harder (2008). The course categories identified
by Benge, Harder & Mashburn (2008) were very similar to those found in this study; however,
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April 20-23, 2011
the previous study failed to recognize specific courses needed including grant writing, statistic
and data analysis, volunteer development, problem solving, teaching methods, group and
organizational leadership. This study also allowed extension education faculty to report courses
taken outside of their department to more accurately reflect the students‟ program of study.
These findings suggest it is important for faculty members to assess their program as a whole,
not just courses offered by the department. They can then require additional courses in their
programs of study that are already being offered by other departments outside of extension
education to improve and further prepare graduates in all the necessary areas.
Future research of specific course content should be conducted to analyze what is actually being
taught and its correlation to competencies. By utilizing the current courses and cross referencing
with the associated skills, professors can evaluate topics to ensure they are teaching the
knowledge and skills necessary for successful careers in Extension and identify areas for
improvement. This exploration also raises the question concerning degree requirements for
entry-level extension agents. While some states only require a Bachelor‟s degree, many are
beginning to require or at least prefer a Master‟s degree for these positions. One Extension
administrator summarized this by saying, “Many of these skills [core professional competencies]
are weaknesses of my Bachelor level employees”. This educational requirement will become
increasingly important as Extension moves into the 21st century. Extension administrators and
professors need to work together in order to structure programs that adequately prepare graduates
with the correct competencies needed to perform successfully. Both should collaborate to design
educational programs as well as internships, experiences, courses, and professional development
offerings. There is also the potential for collaborative efforts to create a pre-professional training
program to further prepare agents for entering the field. If a particular state requires a Master‟s
degree for entry-level positions, this requirement must be publicized and options must be made
available for applicants. In some states, financial waivers are given to Extension professionals to
help them pursue a higher degree indicating that there is associated value placed on a Master‟s
degree. Extension administrators should work with faculty to ensure there are available
opportunities for professional growth. Options to ensure employees gain needed skills may
include collaborative professional development opportunities, pre-professional training programs
or possibly a structured mentor program for new agents. Further research should be conducted
with regard to the current and future collaboration of these two groups in order to identify ways
to improve existing programs and create new ones.
Objective Two
The second objective sought to describe specific job skills related to professional competencies
needed by entry-level extension agents. Extension administrators identified 65 different sub
categories within the 19 competency areas. The results showed that Extension administrators did
not see online social networking and technical expertise as necessary skills for entry-level
extension agents. With regard to technical / subject matter expertise, one respondent
summarized this point well, “[Technical / subject matter expertise] is important but sometimes
not as important as personality and attitude. I‟d rather hire a person with the right personality and
attitude and train them than have one that is technically competent but without people skills”.
Since online social networking did not reach consensus, this indicated that Extension
administrators do not rate online social networking as a critical job skill at this time. As
Extension evolves in changing times, this skill area may become an important component of
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April 20-23, 2011
successful marketing and promotion of programs. Ironically, social networking was one of the
most frequently cited skill areas in Extension administrators‟ responses, yet it did not reach
consensus in the final round of the Delphi. This would be an interesting subject for further
research to examine whether online social networking should be utilized and how it could be
used to reach the next generation of Extension clientele. This also raised questions about how the
professional backgrounds of the Extension administrators aligned with agents‟ backgrounds.
Further research should analyze the type of agents in each participating state including
responsibilities, relationships, and length of employment to give insight into differences.
The 63 skill areas identified serve as a valid resource for both the extension organization and
academia. These skills can be used to make often vague extension job descriptions much more
specific to what hiring entities are looking for in applicants. Also, faculty members can utilize
this list of skills to build lessons, activities, and assignments. Further research should analyze
these specific job skills from the perspective of entry-level extension agents to determine their
agreement, assess whether any skills were missed, and identify specific areas needed for
professional development in their state. Another topic of interest that resulted from the
Extension administrator responses regarding the issue of professionalism was the concept that
often, “Ag agents in particular find professionalism to be a barrier to building relationships
which becomes a problem in being seen as professionals by the community.” The issue of
extension agents sometimes having the “good old boy” mentality in some parts of the country
can definitely hinder the organization by reducing the perceived professionalism of the program.
When an agent is more concerned with being a friend or one of the group than providing
research based information, the validity of the organization is threatened. This topic warrants
further research.
Objective Three
The third objective sought to compare perceptions of the importance of professional
competencies within hiring practices and level of career preparedness. Extension administrators
perceived that entry-level agents were the most prepared in their ability to utilize technology for
program delivery, technical subject matter expertise and communication skills. This indicated
that educational degree programs were adequately preparing students in these areas. Areas in
which students were perceived as being less prepared were development of extramural funding,
program evaluation and volunteer development. These three competencies were also identified
by professors as the areas in which students were least prepared. These similarities indicated
there was agreement among the two groups that graduates were lacking in their preparation for
volunteer development and the development of extramural funding. Additional courses should be
added to address these specific topics or these topics should be added to existing courses within
extension education programs of study. Professional development opportunities in these areas
should be provided for existing agents. These might be valuable topics for existing agents within
states to help mentor and teach to both current agents as well as students. Extension
administrators and faculty members should work together to develop these opportunities and
additions to the current curriculum.
When comparing level of preparedness to the importance Extension administrators place on each
competency during the hiring process, there were differences as well. Administrators ranked
competencies found within the concept of core interpersonal skills to be the most important
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April 20-23, 2011
during hiring; while volunteer development, development of extramural funding, organizational
leadership development, and applied research skills were perceived as less important during the
hiring process. These findings indicate there was a distinct difference in the perceptions of
professors and administrators regarding the preparedness of graduates and new hires. These
differences indicated there may be areas in which graduates need to be better prepared, such as
volunteer development and the development of extramural funding. Either the addition of these
topics to already existing courses or further required coursework should be included in extension
education programs in these areas. Again, collaborative efforts should be made to provide
professional development training to existing agents who find themselves underprepared in these
areas. Extension administrators could also set up a mentorship between new agents and existing
agents who are proficient in these areas for development.
There were both similarities and differences in the rankings of competencies that Extension
administrators said they placed emphasis on during hiring and the level of preparedness of
graduates. The similarities indicated there may be a reflection in extension education programs
based on former hiring practices of Extension administrators. Both extension administrators and
professors indicated that graduates were well prepared in the area of technical and subject matter
expertise, but this competency ranked eleventh in the importance during hiring. The
competencies of volunteer development, development of extramural funding, organizational
leadership development and applied research skills ranked the lowest in the importance during
hiring and were also areas that both extension administrators and extension education professors
ranked lowest with regard to the level of preparedness. Hiring practices is an area that should be
explored through further research. It is important for the future success of Extension that hiring
practices match the skills and competencies that are most important for successful careers. This
issue is also related to the retention of Extension agents. Perhaps by better preparing agents
through education and hiring highly qualified agents with the right skill sets, the organization can
improve the success and retention of agents; thereby reducing the associated costs of agent
turnover. As budget issues continue to plague Extension, administrators are constantly seeking
new avenues to decrease spending. Through collaboration with academia, extension can work
with professors to design appropriate teaching and learning experiences that better prepare future
applicants.
Objective Four
The fourth objective sought to develop a recommended professional framework for extension
education programs at land grant universities. Figures 1 and 2 in the results section outlined the
course categories that were being utilized to teach the specific competencies. The researchers
developed a model (Figure 3) detailing recommendations to allow both organizations to
collaboratively work toward creating career success for extension professionals. This model
utilizes professional competencies and associated skills found in this study as the foundation for
successful extension organizations and educational programs. It employs a stair-step method to
show a possible career preparation path for individuals hoping to have successful careers in
Extension. It asks both Extension administrators and faculty to examine their current practices to
ensure they are providing opportunities for success for entry-level agents. It also calls for both to
work together to achieve these goals and make both organizations better.
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April 20-23, 2011
Figure 3. Model of career success in extension
13
April 20-23, 2011
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An Exploration of College of Agriculture Ambassador Programs
Shannon Arnold, Montana State University
Abstract
Through this qualitative grounded theory study, researchers sought to explore the
structure and organization of ambassador programs with the question: What are the
common components of College of Agriculture ambassador programs? The population
consisted of all four-year public universities with an identifiable College of Agriculture
ambassador program. The sample was derived from the attendance roster of the 2008
National Agricultural Ambassador Conference. A total of 31 ambassador programs and
74 participants were included in the final sample. The advisor and one current student
ambassador were interviewed from each program. Conventional content analysis was
the primary data analysis method (Charmaz, 2003). The study revealed the common
components of an ambassador program as leadership development, promotional
activities, relationship building, student benefits, and presentations. Leadership skills,
academic knowledge, and self-confidence were gained by participation in the many
events offered through the program. A structured retreat and continuous training were
important leadership development components. Being a knowledgeable expert about the
college was a major responsibility as ambassadors attended public events and gave
recruitment presentations. There were many incentives reported that made involvement
worthwhile, including networking with key people. It is hoped that ambassador
programs can utilize results to improve functions and overall student leadership.
Introduction and Framework
Student leadership programs are found in all colleges and universities across the nation.
Over 800 student leadership programs were present on university campuses in the early
2000s and continued to grow annually (Cress, Astin, Zimmerman-Oster, & Burkhardt,
2001; DiPaolo, 2002; Zimmerman-Oster, K., & Burkhardt, J. C., 1999). The purpose of
these programs was not only to serve the mission of the university, but to enable students
to develop personal and professional leadership skills critical for the future (Astin, 1996).
According to Ricketts and Bruce (2008), a new generation of leaders was needed not only
to build partnerships in communities, but to assume positions of leadership in life.
Research has shown that while working to develop leaders for the 21st century, it was
important to encourage skillful communication while promoting cooperation and
understanding (Watt, 2003).
Literature supports the notion that leadership can be learned and as a result, there
continues to be a growing number of formal leadership programs in higher education that
promote socially responsible leadership skills (Scott, 2004; ZimmermanOster&Burkhardt, 1999). Haber (2006) described formal leadership programs as
“intentionally designed learning opportunities aimed at expanding college students’
knowledge, skills, and values” (p. 30). Leadership programs are a unique experiential
learning approach to teach leadership skills due to the variety of educational strategies
utilized, including teamwork, service and experiential learning (Komives, et al., 2006).
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Haber and Komives (2009) found that involvement in student organizations was a critical
experience specifically to enhance leadership development skills, peer engagement,
community involvement, and self-improvement. Hoover (2004) found that participation
in collegiate student organizations can be positively associated with college retention and
satisfaction; student development; increased interpersonal skills; leadership development;
communication, teamwork, organizational, decision making, and planning skills; and
volunteering and community service. Undergraduate student programs can advance
leadership skills in a variety of areas such as problem solving, decision making,
empowerment, planning, organization, and communication (Hoover, 2004). Example
collegiate programs may include freshman orientation, seminars, student body councils,
leadership institutes, public relations activities, academic organizations, and student
recruitment (Zimmerman & Burkhardt, 1999).
Astin’s (1999) student involvement theory predicted that learning increases when
students are more involved in academic and social aspects while in college. An involved
student is one who devotes considerable energy to academics, spends a large amount of
time on campus, actively participates in student organizations and activities, and interacts
often with faculty (Astin, 1984, p.292). Student involvement as defined by Astin is “the
amount of physical and psychological energy that the student devotes to the academic
experience” (p.518). Focus is placed on the behavioral processes that facilitate student
development, as well as the quality and quantity of student involvement in educational
programs. Co-curricular involvement was identified as a significant variable that affected
leadership outcomes related to personality and self-concept. The amount of time spent
engaged in co-curricular activities was positively correlated with producing leadership
qualities and outcomes. Some of the specific measures found to positively affect cocurricular involvement were student-student interaction, student-faculty interaction,
fraternity/sorority membership, and volunteer work. Each of these factors significantly
contributed to leadership growth and development commonly associated with
involvement in student organizations (Astin, 1999).
Leadership development has been extensively researched with many youth organizations,
including FFA and 4-H. The positive impact on improved leadership skills through youth
involvement in camps, projects, conferences, councils, and after school programs has
been documented (Connors & Swan, 2006; Smith, Genry, & Ketring, 2005; Boyd, 2001).
Continued involvement in collegiate programs further develops these life skills. Connors
(1996, p. 312) stated, “For those students who embark on a career in agricultural
education, it is vitally important that they continue to gain valuable experience in a
collegiate agricultural education organization.” Ewing, Bruce, and Ricketts (2009) found
that 434 (55%) of 789 College of Agricultural Sciences students surveyed participated in
a collegiate organization and of those, 184 (23%) held an officer position. Research also
revealed that all students felt that membership in a collegiate organization, whether they
were an officer or not, positively contributed to leadership skill development. Dugan, et
al (2011) researched the influences of program participation on university students’
capacities for socially responsible leadership and found that according to those that
participated in an individual leadership experience, the highest involvement rates were
for lecture/workshop series (72%), conferences (65%), and a single leadership class
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(56%). This research also identified the specific need for additional research on college
student leadership development using qualitative inquiry into the nature of leadership
experiences, the integration of learning experiences, and high impact educational
strategies. College of Agriculture (COA) ambassadors is a unique student leadership
program and course aimed at improving the overall excellence of the college and creating
awareness for agriculture. Ambassador programs are generally composed of agricultural
student leaders who are directly involved with college promotion, recruitment and
retention. Students serve as college representatives at a variety of public relations events
and educate prospective students about university agriculture programs. Serving as the
public face of Colleges of Agriculture requires ambassadors to emulate many leadership
characteristics common in several leadership theories and approaches (Northouse, 2004).
Although there are varying differences in the mission statements of agricultural
ambassador programs, shared features include promotion of the college and its
agricultural degrees, as well as recruitment and retention of students. The mission of
agricultural ambassadors at Montana State University (MSU) is to promote the COA by
providing interactive experiences in careers and technologies as they relate to agriculture
and natural resources. The purpose of the organization is to recruit and retain students in
the COA while instilling a life-long appreciation for agriculture and natural resources
within current and prospective students
(http://www.ag.montana.edu/students/ambassadors.htm). Recently, the MSU’s COA
ambassador membership dropped by fifty percent in one year due to lack of structure and
guidance and the college was considering elimination of the program. Therefore, this
exploratory study was conducted to better understand COA ambassador programs
throughout the nation to gain ideas for program improvement and increase organizational
effectiveness. This study addressed the Agricultural Education in University and
Postsecondary Settings of the National Research Agenda Research Priority 2: Improve
the success of students enrolled in agricultural and life sciences academic and technical
programs.
Purpose
Through this qualitative grounded theory study, researchers sought to explore the
structure and organization of COA ambassador programs across the United States. The
research question that guided this study was: What are the common components of
College of Agriculture ambassador programs? The resultant grounded theory explains
the components of a COA ambassador program. With this understanding, it is hoped that
each ambassador program can improve its functions and overall student leadership.
Methods
The population for the study consisted of all four-year public colleges and universities
across the United States with an identifiable College of Agriculture ambassador program.
The sample consisted of college ambassador programs that were on the official
attendance roster for the 2008 National Agricultural Ambassador Conference. A
purposive sample was utilized as it allows for the choice of people who are “typical” of a
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group and can represent diverse perspectives (Leedy & Ormrod, 2009). The purposive
sample was derived from the attendance roster of 36 universities and approximately 300
students that attended the 2008 National Agricultural Ambassador Conference. This
roster was regarded as a credible source of active and current ambassador programs
representing all areas of the country.
In 2009, MSU COA student ambassadors were assigned to research three or four
university ambassador programs from the list of conference participants. Ten student
ambassadors and the advisor served as the primary researchers for this study. A total of
31 ambassador programs were contacted and participated in the research project. Five
universities on the sample list were unable to be contacted and therefore eliminated from
the sample. COA ambassador programs from the following states were included in the
sample: Alabama, Arizona, California, Colorado, Florida, Georgia, Idaho Illinois,
Indiana, Iowa, Kentucky, Louisiana, Michigan, Mississippi, Missouri, North Carolina
North Dakota, Ohio, Oklahoma, Pennsylvania, South Dakota, Tennessee, Texas
Vermont, and Virginia. The advisor of the ambassador program and at least one current
student ambassador were interviewed from each school. This allowed data to be
collected from both the leader and student perspectives. Seventy-four participants were
included in the final sample.
Data Collection
Telephone interviews served as the primary data collection method in order to obtain an
understanding of the structure and organization of ambassador programs. All researchers
completed IRB training prior to conducting research. All researchers also participated in
a training session conducted by a qualitative researcher to standardize interviewing
techniques and procedures to improve the dependability of the study. The researchers
interviewed both an advisor and at least one student ambassador from each school and
posed open-ended questions. Participants were encouraged to discuss components,
experiences, structure, and organization of the ambassador program.
Interviews were conducted over a four month period and ranged from 30 minutes to one
hour in length with each participant. Questions were created based on the study question,
Astin’s student involvement theory (1999) and Haber and Komives (2009) research.
Questions centered on the following topics: goals, mission, and program objectives;
application and selection process; guidelines and requirements; training programs;
recruitment and retention activities; leadership and service activities; evaluation and
reporting; promotion; funding and support; audiences; challenges and obstacles;
collaboration; interactions; peer engagement; community involvement; and selfimprovement. All participants were asked to share thoughts and perceptions regarding
their experiences and offer suggestions for program improvement.
Researchers utilized a semi-structured interview guide which allowed for more freedom
in questioning and exploration during the sessions (Holstein & Gubrium, 2003). This type
of interview was chosen because it supported the ability for the different researchers to
present initially prepared open-ended questions, but also initiate probing questions based
on the participants’ responses (Wengraf, 2001). Researchers posed all interview guide
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April 20-23, 2011
questions and listened intently while taking field notes. This overall approach proved
beneficial in acquiring detailed explanations to similarly prepared questions, but also
increased the ability to analyze data for significant concepts.
Data Analysis
Field notes and were taken by the researchers, which included key points, direct quotes,
impressions, central concepts, and answers from each question to assist in transferability
of data (Lincoln & Guba, 1985). Then, as a group, researchers combined interview data
and field notes to construct the fullest understanding of data from the participants’
perspectives. All data was triangulated among researchers after the interviews in order to
increase the credibility and confirmability of the collected data (Lincoln & Guba, 1985).
Additionally, each ambassador presented individual findings to the entire group so that
the group could gain an overall understanding of the data. All field notes were content
analyzed based on data and personal interpretation to discover commonalities. A final
data audit was conducted by the primary researcher to examine the data collection and
analysis procedures for bias and distortion to enhance dependability and confirmability
(Lincoln & Guba, 1985).
Conventional content analysis was the primary data analysis method (Charmaz, 2003).
This analysis derives coding categories directly from the data that allows for a richer
understanding of the information. Strategies including a data coding process, constant
comparisons, and refinement of emerging ideas were applied to form the foundation of
the analysis (Charmaz, 2003). Researchers allowed coding categories to emerge from the
data as related to the research question. Initial analysis began with individual open
coding of interview field notes and then researchers coded together as a group to improve
interrater reliability (Leedy & Ormrod, 2009). Common codes were highlighted that
were reflective of thoughts from participants. Codes were then sorted into themes based
on relations and linkages to emergent coding categories. Synthesized themes were used to
contextualize the data and establish clear concepts (Strauss & Corbin, 1990). The
resultant categories were used to create a profile of ambassador programs and a final
report was created to synthesize the results.
Results
The research question that guided this study was: What are the common components of
College of Agriculture ambassador programs? Specific categories that emerged from the
data are discussed and were used to develop a grounded theory of a COA ambassador
program (Figure 1). The main components of a COA ambassador program as reported
from the data include leadership development, promotional activities, presentations,
student benefits, and building relationships.
Leadership Development
Leadership development was a common theme identified by all ambassador programs.
Nearly every program interviewed provided a leadership retreat most commonly one to
three days prior to the start of fall semester. Some schools even expanded the retreat to
be held in collaboration with other agricultural ambassador programs from the same or
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April 20-23, 2011
neighboring states. Participants stated that this provided an opportunity to complete team
building activities, network with other ambassadors, and gain ideas for the upcoming
year. The retreat was also considered the optimal time to train new members and orient
the team with the year’s activities. A strong training program was considered vital to the
success of the ambassador program as it provides members with an understanding of
expectations, the ability to speak knowledgably about university degrees and programs,
and the confidence to enter a classroom or event to represent the College of Agriculture.
Additional topics covered during the training included setting individual and group goals,
providing members updated information on the university and college, and scheduling
major events. All programs except one send representatives to the National Agriculture
Ambassador Conference, which they said was a great way to “be proud of your own
program while visiting with other ambassadors across the nation on ways to improve.”
As part of the leadership development process, the selection of ambassadors was also
discussed. This activity varied among schools. Many schools had a formal selection
process where students were required to interview with current ambassadors and faculty
for a specific number of positions, while others allowed open program enrollment. The
size of ambassador organizations varied from 10- 100 students. This process was seen by
many participants as a critical program component to ensure that student leaders were of
high quality.
Promotional Activities
COA ambassador programs found that as the economy declines, so does the opportunity
to travel and recruit at high schools and events across the nation. Ambassador groups
have individually tried to overcome such obstacles by mainly targeting junior colleges,
recruiting at regional activities, hosting invitational events, and visiting secondary
schools close to home. Public appearance was identified by participants as one of the
most important parts of being an ambassador. On and off-campus activities and tours
were common across all ambassador programs. Having positive public interactions and
representation at university events was critical to promotion. Many programs were
frequently involved in alumni events, fundraising functions, and conventions as the face
of the College of Agriculture. One participant stated, “We embrace the opportunity to be
more involved in these events as it is vital that donors and others see and speak with
current COA students. As agriculture ambassadors, we have a more visible appearance
so others know not only what we do, but who we are.” Many programs were involved in
hosting a large on-campus event for potential students once or twice a year. Being
involved in on-campus agricultural events, such as the State FFA convention, Ag Days,
and 4-H Congress, provided an excellent opportunity to reach large numbers of younger
audiences without having to travel. One participant stated,
We hope to strengthen our presence at these activities and let people know that we
are available to provide tours and meet with students throughout the year.
Additionally, while not as visible, we need to follow-up on these contacts with
personal phone calls to potential students. Having someone know we are
interested in them as an individual and a student could make a difference in where
their tuition dollars are spent.
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April 20-23, 2011
As an event host, some programs provided students with a group lunch while others had
ambassadors meet with each prospective student. In addition, there were also
opportunities for students to stay in the dorms or spend the night with an ambassador. A
few schools instituted a more personal on-campus event that consisted of an application
process to select extremely high caliber students that were then invited to campus.
Priority for off-campus recruitment was placed on agricultural secondary students and
junior colleges. These audiences were considered to be the most cost-effective since
students already have an identified interest in science and agriculture. By targeting
district FFA competitions, 4-H meetings and workshops, livestock judging contests, 4-H
Congress, science competitions, and other agriculture or science-based events, the
audience was more likely to be interested and receptive to ambassador presentations than
a group of general students. To reduce costs and the amount of time missed during the
semester, ambassadors are encouraged to visit a high school within their home area
during breaks. This can also increase effectiveness of the presentation due to already
established school connections.
Presentations
To increase program efficiency and provide clear, distinguished messages, standardized
presentations about the College and its degree programs were utilized by many
ambassador programs. Some have specific academic degree presentations for each
department that are readily accessible and user friendly. One participant stated, “These
presentations are valuable so that if a potential student arrives interested in agricultural
education, then, for instance, an available plant science ambassador can open the
agricultural education powerpoint and knowledgably walk through it with a student.”
Ambassadors work closely with faculty to develop interactive presentations suitable for
small and large groups. By offering presentations that create awareness of the
opportunities available within the College of Agriculture, ambassadors can appeal to both
traditional and non-traditional agricultural students.
Students Benefits
Advisors and students all agreed on the extensive time commitment required to serve as
an ambassador. However, the personal and professional rewards of being an ambassador
were numerous. Many commented on the leadership development, communication, and
self-confidence gained as a result of serving as an ambassador. External incentives
varied among universities. Common examples included class credit, academic
scholarships, early class registration, travel opportunities, or “incentive gifts”, such as
computer accessories, college paraphernalia, or journals, for top students. For many, the
ability to travel all over the state and attend the National Agricultural Ambassador
Conference and were valued rewards. Nearly every school interviewed strongly
recommended that all ambassador programs attend this conference to gain recruitment
ideas and network with other students.
Building Relationships
Building relationships was commonly identified as an important factor for programs to
succeed. The most important relationships identified were those with faculty, the Dean,
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April 20-23, 2011
department heads, and admissions. Relationships were identified as critical to help reach
larger groups of students for recruitment and retention purposes.
Having strong relationships with the Dean was important in all ambassador programs.
By maintaining connections with the office, each program was able to be recognized,
utilized, and funded as a recruitment resource. The majority of participants felt the Dean
realized the importance of the ambassadors and their impact. Budgets were primarily
funded through the Dean and ranged from $3,000 - $50,000 per program. Some schools
were provided a set dollar amount per student in the college, while others were provided
funds when needed. Overall, participants felt that they had access to adequate funds
needed to complete their recruiting and retention goals. One common experience among
programs was to meet with the Dean annually to learn about the goals and outlook for the
College and discuss how ambassadors can aid in the process.
There was a variation of activities that each program engaged in to assist in building
relationships with faculty and department heads from panel discussions to interviews to
class visits. Faculty commonly assisted in the nomination and selection process,
provided access to non-agriculture students, promoted the activities of ambassador
programs, and served as key speakers. Other roles that faculty assumed were to assist in
designing science based presentations, offer technical content, provide updates on
departmental news, academic programs and research, and give recommendations of
potential students and ambassadors. Working with the admissions office was also
considered to be an important connection. Through this relationship, ambassadors had
contact with potential agriculture students who contacted the campus instead of the
college. Ambassadors worked closely with the admissions office to speak with students
interested in agriculture and offer specialized tours. Some programs worked closely with
the university tour guides and offered training on the College of Agriculture to have a
better understanding of its programs.
Leadership
Development
Promotional
Activities
Presentations
COA
Ambassador
Program
Relationship
Building
Student
Benefits
Figure 1. Grounded theory of a College of Agriculture ambassador program
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April 20-23, 2011
Conclusions, Recommendations and Implications
Collegiate student organizations are a key component of Astin’s (1984) theory of student
involvement and undergraduate education. The organizations offer a multitude of
opportunities for interactions and volunteerism which correlate with positive leadership
development and personal growth. However, these programs must be structured around
experiential learning to build essential leadership qualities (Komives, et al., 2006). COA
ambassador programs have the ability to offer a wide variety of activities to engage
students in developing interpersonal, professional, and leadership skills. This study
revealed the common components of an ambassador program as leadership development,
promotional activities, relationship building, student benefits, and presentations. It was
reported that leadership skills, academic knowledge, and self-confidence were primarily
gained by participation in the many events offered through the program. Involvement in
these social and academic activities has been proven to build critical leadership skills
reported by Hoover (2004) and Astin (1999).
A structured retreat, coupled with continuous training, were important components to
each ambassador program. This allowed the team to become a more cohesive unit,
particularly for first year members to network with veteran ambassadors. The retreat
offered time to practice presentations, learn updated information, and establish peer
mentoring relationships. By providing an opportunity for members to get to know one
another better, the group can become more unified and focused on their mission.
Additionally, hosting a retreat or exchange with neighboring ambassador programs can
help develop ongoing connections for the future.
Being a knowledgeable expert about the college and university was a major responsibility
of each ambassador. Presentations focus on general information about the university, the
College and its related majors, degree options within each department, and student
organizations and clubs. Additional information to answer frequently asked questions
from potential students about campus events, financial aid, and residence life might also
be beneficial to discuss. During the year, training should continue so each ambassador
can present a standard presentation about each department with confidence. A working
binder of university and college information that is updated annually could also be
created to educate new members quickly to gain the knowledge needed to be successful
at the first events. Continuing education should also include the addition of guest
speakers, specialists, industry members, alumni, and administrators to the meetings. By
bringing in experts, members can become familiar with all programs, versus just their
own. While it is realistic to learn facts and figures, hearing firsthand about each
program’s benefits, current research, teaching, outreach, and career opportunities can
provide prospective students with additional information beyond the standard pamphlets.
The inclusion of different types of teaching and learning activities must be included by
the advisor to assist all members in building knowledge in these many areas.
Promotional activities varied among programs, but focused on career showcases, junior
colleges, regional events, middle and high schools, outreach events, agricultural
conventions, and public meetings. The majority of off-campus recruiting was conducted
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in agriculture and science classes at high schools and junior colleges. However, as
budgets continue to decrease at many universities, ambassador programs must develop a
more economically feasible recruitment strategy to replace visits around the state.
Hosting on-campus invitational events was one way to gain access to large numbers of
potential students. A specific recruitment event with tours, workshops, industry speakers,
and meetings with faculty and students can be more cost effective than traveling. Having
a structured career day where students can participate in a college class or spend time
with ambassadors can make the event more personal and influential. Many participants
also mentioned the importance of being involved with alumni events. Staying connected
with alumni can help to multiply recruitment efforts and connect with remote
communities. If provided with sufficient information, alumni could be used to promote
the College at their local events and schools.
One participant stated, “To be an agricultural ambassador takes an extensive amount of
time, energy, and effort in addition to schoolwork and other activities.” Yet, there were
many student benefits and incentives reported that made involvement worthwhile. The
development of self-confident, leadership, interpersonal, and communication skills were
common reasons, in addition to the opportunities to build relationships. The ambassador
program’s unique mission as the face of the College enables members to create key
relationships within the college, university, industry and communities. Having an
opportunity to work with leaders in all areas can help to build both personal and
professional references for members. These relationships can be beneficial as students
search for internships and future careers. Additional opportunities for professional
development that were appreciated included traveling to local, regional, state, and
national events. The ability to attend the National Agriculture Ambassador Conference
to learn more about ambassador programs around the nation was considered a highlight
experience and should be considered as an annual activity.
The selection process of student ambassadors ranged from formal to informal, although
the majority held interviews. By having a more formalized selection process, program
members can identify the strengths of each applicant and their commitment to the
organization. An informational session held for interested students prior to the
application deadline could be valuable so they can learn about the requirements of the
organization, ask questions, and evaluate their fit. Top applicants could then be selected
for the interview process which could include stations to showcase personal strengths
such as team building, leadership, and public speaking.
Interestingly, very few programs discussed the topic of retention of current COA
students. Although all did not have this in their mission statement, it was a central
component of many programs. The majority stated that on-campus events and mentoring
relationships were the main retention activities conducted. The lack of detailed
discussion about retention of student warrants further research. Questions about retention
activities, focus, importance, and impacts should be asked to determine what is currently
being done.
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April 20-23, 2011
After interviewing ambassador programs from across the nation, the MSU College of
Agriculture Ambassadors implemented the findings to improve the current program. A
complete restructuring in the areas of selection, training, activities, and requirements was
initiated. The selection of new ambassadors now includes a carousel interview process of
various stations, such as team building, personal interview, case scenarios, student
questions, and impromptu speeches, judged by current Ambassadors and COA faculty.
This not only assists in recruiting quality students, but provides exposure of the program
to other departmental faculty. Retreats and trainings have been re-designed to build
knowledge, leadership, and presentation skills. An annual weekend retreat, new
ambassador trainings, socials, a training binder, impact statements, and leadership
updates have been established as requirements. In 2011, the MSU ambassadors worked
in collaboration with neighboring states to create a two day Northwest Regional
Ambassador Conference that included professional development, educational workshops,
campus tours, and idea exchanges. Modeling the program after other universities, the
ambassadors developed a recruitment and retention plan to be more effective with
available funds. This included attending regional events, increased participation in oncampus and alumni events, and the development of a public COA off-campus tour. A
professional, quality recruitment board and retractable display banners were developed
with a graphic designer to promote a unified college image. Improved relations with the
Admissions office through Phone A Thons, the development of a COA tour booklet, and
training of university representatives on the COA has created more educated recruiters
overall. Recruitment items including MSU Jeopardy, Plinko, and a miniature golf game
have also assisted in generating more booth interest at career events. Retention activities
continue to be a work in progress with ideas for more student-faculty interactions and
events, collaborative organizational activities, a peer mentoring program, utilization of
community alumni, and increased public presence at agricultural events. Student
involvement in undergraduate organizations, such as the COA ambassadors, has mutual
benefits both to the student and the college. By continued engagement in these events,
students develop a greater appreciation for the college which can lead to increased
retention for the college (Hoover, 2004). Advisors should continue to promote student
involvement and co-curricular activities to enhance the total collegiate experience for all.
11
April 20-23, 2011
References
College of agriculture ag ambassadors[Online information request]. Retrieved from
http://ag.montana.edu/students/agambassadors.htm.
Astin, A.W. (1984). Student Involvement: A developmental theory for higher education.
Journal of College Student Personnel, 25, 297-308.
Astin, A. W. (1993). What matters in college?: Four critical years revisited. San
Francisco: Jossey Bass.
Astin, A. W. (1999). Student involvement: A developmental theory for higher
education. Journal of College Student Development, 40(5), 518-529.
Astin, H. (July-August 1996). Leadership for social change. About Campus, 107.
Boyd, B. (2001). Bringing leadership experiences to inner-city youth. Journal of
Extension, 39(4). Retrieved from http://www.joe.org/joe/2001august/a6.php.
Charmaz, K. (2003). Grounded theory: Objectivist and constructivist methods. In
Denzin, N. K. & Lincoln, Y. S., Strategies of Qualitative Inquiry. Thousand
Oaks, CA: Sage
Cress, C. M., Astin, H. S., Zimmerman-Oster, K., & Burkhardt, J. C. (2001).
Developmental outcomes of college students’ involvement in leadership
activities. Journal of College Student Development, 42(1), 15-27.
Connors, J. J. (1996). Current status of agricultural education organizations. Proceedings
of the National Agricultural Education Research Meeting, USA, 23, 312-320.
Connors, J. Swan, B. (2006). A synthesis of leadership development research in
agricultural education: 1988-2003. Journal of Agricultural Education 47(2). doi:
10.5032/jae.2006.02001
DiPaolo, D. G. (2002). Voices of leadership. Ann Arbor, MI: University of Michigan.
Dugan, J. P., Bohle, C. W., Gebhardt, M., Hofert, M., Wilk, E., & Cooney, M. A. (2011).
Influences of leadership program participation on students’ capacities for socially
responsible leadership. Journal of Student Affairs Research and Practice, 48(1),
65–84. doi:10.2202/1949-6605.6206
Ewing, J., Bruce, J. & Ricketts, K. (2009). Effective leadership development for
undergraduates: How important is active participation in collegiate
organizations? Journal of Leadership Education, 7(3), 131-143.
12
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Haber, P. (2006). Structure, design, and models of student leadership programs. In S. R.
Komives, J.P. Dugan , J. E. Owen, C. Slack & W. Wagner (Eds.), Handbook for
Student Leadership Programs (pp. 29-51). College Park, MD: National
Clearinghouse for Leadership Programs.
Haber, P. & Komives. (2009). Predicting the individual values of the social change
model of leadership development: The role of college students’ leadership and
involvement experiences. Journal of Leadership Education, (7)3,133-165.
Holstein, J., & Gubrium, J. (Eds.). (2003). Inside interviewing: New lences, new
concerns. Thousand Oaks, CA: Sage.
Hoover, T. S. (2004). Leadership characteristics and professional development needs of
collegiate student organizations [Electronic version]. NACTA Journal, 48(2).
Komives, S. R., Dugan, J. P., Owen, J. E., Slack, C., & Wagner, W. (Eds.) (2006).
Handbook for student leadership programs. College Park, MD: National
Clearinghouse for Leadership Programs.
Leedy, P. D. & Ormrod, J. E. (2009). Practical research: Planning and design (9th ed.).
Upper Saddle River, NJ: Pearson Education, Inc.
Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage.
Northouse, P.G. (2004) Leadership theory and practice. Thousand Oaks, CA: Sage
Publications.
Ricketts, K. G., & Bruce, J. A, & Ewing, J. C. (2008). How today’s undergraduate
students see themselves as tomorrow’s socially responsible leaders. Journal of
Leadership Education, 7(1), 24-41.
Scott, D. (2004). Are campus leadership programs producing the leaders society needs?
NetResults. Retrieved from
http://www.naspa.org/membership/mem/pubs/nr/default.cfm?id=1351.
Smith, T., Genry, L. & Ketring, S. (2005). Evaluating a youth leadership life skills
development program. Journal of Extension, 43(2). Retrieved from
http://www.joe.org/joe/2005april/rb3.php.
Strauss, A., & Corbin, J. (1990). Basics of qualitative research. Newbury Park, CA:
Sage.
Watt, W. M. (2003). Effective leadership education: Developing a core curriculum for
leadership studies. Journal of Leadership Education, 2(1), 13-26.
Wengraf, T. (2001). Qualitative research interviewing: Biographic narrative and semistructured methods. Thousand Oaks, CA: Sage.
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Zimmerman-Oster, K., & Burkhardt, J. C. (1999). Leadership in the making: Impact
and insights from leadership development program in U.S. colleges and
universities. Battle Creek, MI: W. K. Kellogg Foundation.
14
April 20-23, 2011
An Investigation of Pre-service
Agriscience Teacher Stress Levels, Gender, and School Size
Rudy Ritz
Abstract
The purpose of this study was to examine stress of agricultural science pre-service
instructors in the teacher education program at Texas Tech University. The target population
for this study was secondary agricultural science student teachers in the field experience prior to
graduation. Agricultural education student teachers included in this study were completing the
experience in school classroom placement at the secondary level. A total of (n = 19) beginning
teachers from the spring 2010 semester were identified. There was a 100% response among the
19 teachers. Descriptive information included more than one half of the sample consisted of
females. Additionally, most of the pre-service teachers involved in the study were obtaining the
experience in smaller schools. One fourth of the student teachers were placed in large schools
having an enrollment of more than 1000. The researcher explored pre-service teachers’ gender
and school size for possible relationships among the ten stress factors in the Teacher Stress
Inventory (TSI), a 49-item instrument used to measure stress levels among teachers (Fimian &
Fastenau, 1990). Overall, the pre-service agriscience teachers reported barely noticeable
stress. Work-related Stress, one of the ten TSI factors, exhibited a relationship of magnitude
among the participants’ gender and the school size.
Introduction and Theoretical/Conceptual Framework
Professional development efforts targeting areas such as job satisfaction, stress, and time
management are a reasonable approach to possible burnout, particularly with beginning teachers
(McLean & Camp, 2000). The induction year of professional development and university
preparation’s role in teacher education has been the traditional approach to training, via the
student teaching experience. Research questions of student teacher placement and school size
may need exploration. Gender, work environment and the placement or locale may have some
repercussions on the student teaching experience. More females are entering the agriscience
classroom (Burris & Keller, 2007).
The teacher shortages in our public school system have been occurring at an alarming
rate (U.S. Department of Education, 2009). Some school districts employ teachers who lack
proper certification due to a shortage of teacher education program graduates who decide to
pursue a teaching career. There have been reported shortages of qualified agriscience teachers
(Kantrovich, 2007).
The National Council for Agricultural Education 10 X 15: The Long Range Goal for
Agricultural Education, has set goals including growing the number of agricultural education
programs from 7,200 to 10,000 by the year 2015 (National FFA, 2008). A goal of more
programs increases demand for trained teachers. Prioritizing teacher recruitment and retention
April 20-23, 2011
must be an area of focus to attain the goals of the 10 x 15 endeavor. Teacher education
programs exploration of retention techniques include stress factors (Croom, 2003).
Stress, defined by Maslach (1982), is the body’s reaction to change which may be
physical or environmental. Maslach, noted for research involving stress and burnout, identified
the categorical stages of stress: emotional exhaustion, depersonalization and reduced personal
accomplishment. The condition of burnout is a result of unrelieved stress which eventually
prevents the individual from any feeling of personal accomplishment. Working conditions,
emotional or physical, cause stress. Elimination of stress as a solution is not possible according
to Maslach. Control and prevention of becoming overstressed is the approach. Maslach
provided a clear explanation of the job-related stressors of working with people. School
teachers, for example, have the emotion of caring and may suffer the consequences of the stress
from the emotional demands of the job. Combined with work and family balance, the emotional
levels as a result of any occupational strain could lead one to reach a level of frustration or high
stress (Maslach, 1982).
Pressing issues have surfaced in agricultural education including managing stress,
balancing work and personal life, and time management (Myers, Dyer, & Washburn, 2005).
Research conducted on the inservice needs of agricultural science teachers found that teacher
stress and time management were issues needing attention in teacher professional development
(Roberts & Dyer, 2004). The statewide study consisted of both traditional and alternatively
certified teachers. Roberts and Dyer found teacher stress and time management as the largest
professional development concerns among both of the sample groups.
Burnout, as a result of unrelieved stress, should be addressed early. A bad experience
while student teaching may prevent many university graduates from entering the teaching
profession (Osborne, 1992). The strategy used to resolve or prevent stress and conflict in the
agricultural education setting may help retain some quality teachers (Croom, 2003). Croom
concluded that as teachers gain experience teaching, they cope to alleviate work-related stress.
Croom and Moore (2003) found moderate stress among young teachers and also reported
experience as a coping tool. The researchers recommended “It would be valuable to study the
ways that teachers are socialized into the teaching profession and inoculated against some stresscausing agents” (p. 271). Stress-causing agents of the workplace have appeared to be a surprise
to beginning teachers. According to Walker, Garton, and Kitchel (2004), additional assignments
on campus are often a surprise reality for new teachers at the secondary level. Teachers in the
beginning year or two of the agricultural education profession were found to have difficulty with
the break-in period. Stages of burnout with beginning teachers may be amplified compared to
seasoned teachers and cause a desire to leave the profession (Walker et al., 2004) (Cheney,
2007).
The factors which determine stress must be addressed taking a professional development
approach (Walker et al., 2004). Torres, Lawver, and Lambert (2009), conducted a study on jobrelated stress and found that hours per week at work was the largest predictor of stress. Meister
and Melnick (2003) concluded that 84% of new teachers reported feeling “overwhelmed by the
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April 20-23, 2011
workload” and recommended that “time management is another area where teacher preparation
programs need a greater focus” (p. 92).
Researchers in agricultural education recommend professional development involving
stress control take place for beginning teachers in the university programs (Croom & Moore,
2003). Croom (2003) recommended teacher education programs should instruct the students
about the potential for burnout. Additionally, the researcher recommended that the induction
instructors be provided with suggestions and strategies for coping with stress causing factors in
the teaching profession prior to entering the beginning teaching job (Croom, 2003).
The purpose of this study was to describe stress levels of agricultural science student
teachers in the teacher education program at Texas Tech University. The following research
objectives were employed to guide this study:
1. Describe the agriscience pre-service teachers.
2. Determine the levels of stress of the pre-service teachers.
3. Explore possible relationships involving pre-service teacher stress, pre-service teacher
gender, and school enrollment/size.
Methods/Procedures
This study employed survey research in order to complete the three objectives. The
target population for this study consisted of secondary agricultural science student teachers from
the university agricultural education teacher preparation program. There was a convenience
sample of all of the spring 2010 semester student teachers for a total of 19 (n = 19). Student
teachers experienced the secondary classroom and additional responsibilities of an agriscience
teacher for a period of 12 weeks.
Limitations of this design include that the study does not control for threats due to
individual characteristics (Frankel and Wallen, 2006). Another limitation of this study includes
sample size. This study included a convenience sample of student teachers. It was a fairly small
group in comparison to the entire population. Caution should be taken to generalize or making
any inferences beyond the scope of this study.
The procedures for the instrumentation involved web-based questionnaires and
electronically delivered reports. The links accompanied by instructions were sent to the teachers
along with an explanation of confidentiality of their response. Strategically, the researcher
designated the timeline of the data collection in order that it transpired through the final week of
the student teaching experience. The researcher obtained a 100% response rate of the 19
participants (n = 19).
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April 20-23, 2011
The Teacher Stress Inventory (TSI) was used to measure the stress levels (Fimian &
Fastenau, 1990). Fimian and Fastenau defined the ten factors of the 49-item TSI: Professional
stress is how teachers see themselves as professionals. Behavioral manifestations are defined as
inappropriate ways to deal with stress. Time management is the “balancing act” related to
teaching. Discipline and motivation are aspects of the teacher-student relationship. Emotional
manifestations are ways that teachers respond emotionally to stress. Work-related stress consists
of environment-specific events that are sources of stress. Gastronomical manifestations are
stomach ailments related to stress. Cardiovascular manifestations are cardiovascular problems
associated with stress. Fatigue manifestations are fatigue problems associated with stress.
Participants rated each statement on a five-point scale including: 1) not noticeable, 2) barely
noticeable, 3) moderately noticeable, 4) very noticeable and 5) extremely noticeable (p. 155).
Reliability was reported by a study conducted on 10-year aggregate data collected by the
TSI authors (Fimian & Fastenau, 1990). The Cronbach’s alpha coefficients for individual
factors/constructs were all greater than 0.75 and there was an overall alpha coefficient of 0.93.
Fimian & Fasteneau conducted factor analyses on the TSI to refine the instrument.
A brief descriptive section including gender of the participants was included to describe
the beginning teachers. School size was also reported by the participants according to categories
for enrollment in secondary schools which are recognized by the state (University Interscholastic
League, 2010). Age was not included in the instrumentation. Mean scores, and standard
deviations were used to analyze data which measured stress levels of the 19 (n = 25) agriscience
teachers.
The researcher explored possible relationships between TSI factors, gender and school
size. Point-biserial and Spearman rank-order correlation coefficients were computed for gender
and school size respectively. The researcher referred to the Davis Conventions (1971) to
describe the magnitude of the correlations. However, inferences were not made as a result of the
design of this study and the convenience sampling methodology of the pre-service teacher group.
Caution should be taken in generalizing beyond the scope of this study.
Findings/Results
Research Objective 1. Describe the agriscience, pre-service teachers.
Almost two-thirds of the pre-service instructors were female (see Table 1). The males
consisted of just more than one third of the group, with seven (36.8%). Age data and other
demographics were not collected in this study due to the convenience sample and the sample
size. Table 1 displays the data for pre-service teacher gender. Additionally, the categorical
school size data, by enrollment, are included in Table 1.
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April 20-23, 2011
Table 1
Summary of Descriptive Data of Spring Pre-service Teachers (N = 19)
f
Demographic
%
Gender
Female
12
63.2
Male
7
36.8
1A (199 & below)
8
40.2
2A (200 to 429)
3
16.0
3A (430 to 989)
3
16.0
4A (990 to 2064)
1
5.0
5A (2065 & up)
4
21.0
School Size – secondary enrollment
Teaching experience among the student teachers included small schools (199 students
and below) to large schools (more than 2065) among the pre-service teachers’ placement
secondary school locations. The pre-service teachers reported school size/enrollment in a range
of student teaching placement stations including all of the five enrollment categories according
to classification levels recognized by the state (see Table 1). Just more than 25% of the preservice teachers were in large schools. The school sizes displayed on Table 1 included the
categories ranging from 1A to 5A. The categorical information was for readers to be aware of
how the state describes enrollment
Research Objective 2. Determine the level of stress of the pre-service agriscience teachers.
There were ten factors or constructs in measuring the teachers’ level of stress. The stress
level of the beginning agriscience teachers was measured by the 49-item Teacher Stress
Inventory (TSI) (Fimian & Fastenau, 1990). The TSI data by the 10 factor means are depicted in
Table 2. The mean for the pre-service teachers’ overall stress on the TSI was M = 2.31 (SD =
0.47).
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April 20-23, 2011
Table 2
TSI Mean and Standard Deviation by Stress Factor (N = 19)
M
TSI Factor
SD
Rank
Discipline & Motivation
3.29
0.78
1
Time Management
2.79
0.85
2
Professional Distress
2.57
0.75
3
Work- Related Stress
2.54
0.52
4
Emotional Manifestations
2.52
1.05
5
Fatigue Manifestation
2.50
0.96
6
Professional Investment
2.26
0.62
7
Cardiovascular Manifestations
1.89
0.97
8
Behavioral Manifestations
1.42
0.52
9
Gastronomical Manifestations
1.33
0.44
10
Note. 1 = Not Noticeable; 2 = Barely Noticeable; 3 = Moderately Noticeable; 4 = Very
Noticeable; 5 = Extremely Noticeable.
For the readability of the mean scores, the researcher listed the ten TSI factors ranked in order
with the more noticeable stress factors ranked first (see Table 2).
Therefore, the overall stress is reported by pre-service agriscience teachers as being in the
range of barely noticeable stress according to the mid-point on the TSI five-point, Likert-type
scale. Six of the constructs in the TSI measured above the noticeable level, or TSI factor means
of more than 2.50 on the five-point scale. Discipline and Motivation was the only TSI factor
mean score where respondents measured above the Moderately Noticeable level on the scale.
Research Objective 3. Explore possible relationships involving pre-service teacher stress, preservice teacher gender, and school enrollment/size.
Although sampling methods in this study limit inference, the researcher designated
exploring the possible relationships between TSI factor mean scores, gender and school size
5
April 20-23, 2011
characteristics (see Table 3). Mean scores of the stress data and the gender of the participants in
the study were analyzed. The researcher computed Point-biserial correlation coefficients for
gender. TSI Mean scores and school size data were analyzed. Spearman rank-order coefficients
were computed for school size based on enrollment information. Table 3 illustrates the 10 TSI
factors and the correlation coefficients for the two characteristics: gender and school size.
Table 3
TSI Mean and Correlation Coefficients by Gender and School Size (N = 19)
Gendera
School Size
rpb
rs
0.21
-0.02
-0.01
-0.10
Professional Distress
0.26
-0.21
Work Stressors
0.62
-0.49
Emotional Manifestations
-0.15
-0.23
Fatigue Manifestation
-0.17
0.02
Professional Investment
0.34
-0.44
Cardiovascular Manifestations
0.08
-0.06
Behavioral Manifestations
0.33
0.08
Gastronomical Manifestations
0.08
0.07
TSI Factor
Discipline & Motivation
Time Management
a
Coding for data: 1 = female and 2 = male
According to conventions in the behavioral sciences (Davis, 1971), a positive or negative
correlation coefficient of 0.01 to 0.09 is negligible, 0.10 to 0.29 is low, 0.30 to 0.49 is moderate,
0.50 to 0.69 is substantial, and greater than 0.70 is very strong.
Findings as a result of the computation of the point-biserial correlation coefficients
exhibited strong magnitude between gender and the TSI factor of Work-Related Stress. The
analysis on gender and TSI mean scores produced a point-biserial coefficient of r = 0.62,
showing a substantial relationship between gender and the Work-Related Stressors. The
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April 20-23, 2011
remaining point-biserial correlation coefficients resulted in negligible to low magnitude
relationships (r = 0.01 to r = 0.29).
Spearman rank-order correlation coefficients were computed for the ordinal data
designating the school size. As a result of the analysis, the reported school size data analysis
produced a negative, but a large medium, Spearman rank-order coefficient of r = -0.49 with the
Work-Related Stress TSI factor mean scores. Again, a correlation coefficient greater than
positive or negative 0.50 is considered large (Davis, 1971). The remaining Spearman rank-order
correlation coefficients in the findings determined there were negligible to low magnitude
relationships (r = 0.01 to r = 0.29).
Conclusions, Implications, and Recommendations
This study conducted descriptive investigation involving a group of pre-service
agriscience instructors from Texas Tech University. Almost two-thirds of the pre-service
agriscience teachers of the 2010 spring semester were female. According to literature, the
amount of females entering the agriscience classroom has increased and this study’s sample
represents that distribution. The number of females in sample exceeds previous findings in the
state where female teachers made up almost one half of the beginning agriscience teachers
(Burris & Keller, 2007). This convenience sample implies that females are very interested in a
career in secondary agricultural education. Although females are beginning to no longer be
perceived as non-traditional in the agricultural education profession, the profession is reminded
that teacher education efforts should improve through exploration and research in working with
students who may be classified as “non-traditional” among agriscience teachers.
The study’s findings on school size characteristics included a distribution across the five
enrollment categories in the state. Almost three-fourths of the pre-service teachers in this study
were experiencing pre-service teaching in small schools with enrollments of less than 1,000 (1A,
2A and 3A as designated by state categories) students in the high school. The remaining student
teachers experienced larger schools with enrollments ranging from 430 students (3A) to more
than 2,000 (5A). However, the participation in larger, non-rural schools by one fourth of the
teachers implies that pre-service teachers are willing to enter the urban environment and face
higher enrollments. The urban setting can be much different than the background of some preservice agriscience teachers.
Possible relationships were considered by the researcher between the gender of the
agriscience teacher and the TSI scores. Correlation coefficients found negligible to low level
relationships between nine of the TSI factors and gender according to Davis (1971). Although
there was no inference made due to the sampling procedures in this study, the researcher gained
interest in the strong relationship between gender and Work-related Stress, one of the 10 factors
of the TSI. Work-Related Stress had a tendency to increase among the males. Work-related
stress consists of environment-specific events that are sources of stress (Fimian & Fastenau,
1990). This implies that the males included in this study possibly approached the student
teaching experience with different expectations or anticipation than did the females. This finding
is not consistent with a related study conducted by Croom (2003), where gender did not
influence beginning teacher responses on burnout.
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April 20-23, 2011
Similarly, Correlations on TSI factors and the school size data, according to the preservice teacher responses, resulted in negligible to moderate levels on nine of the TSI factors.
However, one Spearman-rank order correlation coefficient represented a negative relationship of
magnitude among school size and Work-Related Stress. As school size by enrollment decreased,
there was an increase in the factor of Work-Related Stress. Working in a small school may the
environment specific event as noted in the definition of the TSI factor by the authors (Fimian &
Fastenau, 1990). Potential implications include that the small secondary schools only employ
one agriscience teacher. The presence of only one agriscience teacher most likely requires more
time per professional to conduct the responsibilities toward an effective agriscience program.
Possible stress-causing time variables coincide with findings from Torres, Lawver, and Lambert
(2009), who concluded that hours per week at work was the largest predictor of stress.
The researcher recommends future investigation, involving larger samples, on the effects
of gender on the student teaching experience and work stress. Retention of quality professionals
must begin at the pre-service stage of professional development through skill development in
stress management (Croom & Moore, 2003). While female agriscience teachers maintain a
stronger presence in the profession, there are studies where work and family balance is a variable
becoming more noticed as a professional development concern and as a teacher attrition factor
(Roberts & Dyer, 2004; Cheney, 2007). Furthermore, it is recommended that university teacher
education programs in larger states explore if there are any regional differences for effects on the
experience of student teacher based on gender and geographical placement.
As a result of this study and the research findings, questions arise on the effects of school
size and student enrollment on pre-service teacher field experience. Research on a statewide
level, or possibly a national level, should occur to examine the pre-service teachers’ experience.
School size along with student enrollment data from a larger perspective will allow the
profession to make scholarly decisions toward program improvement or development. There
may be a need for pre-service agriscience teachers to receive some programming and instruction
on school and community issues, including the relevance of school size and its relationship to
teacher workload. Moreover, the number of agriscience teachers in the program serving as a
cooperating student teaching station surfaces as a question for further exploration.
8
April 20-23, 2011
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Meister, D. G., & Melnick, S. A. National new teacher study: Beginning teachers’
concerns. Action in Teacher Education. 24 (4), 87-94.
Myers, B. E., Dyer, J. E., & Washburn, S. G. (2005). Problems facing beginning agriculture
teachers. Journal of Agricultural Education. 46 (3), 45-55.
Mundt, J. P., & Connors, J. J. (1999). Problems and challenges associated with the first years
of teaching agriculture: A framework for pre-service and inservice education. Journal of
Agricultural Education. 40 (11), 38-48.
National FFA Organization (2009). FFA Facts and Statistics. Education. Retrieved
January 19, 2009, from http://www.ffa.org/index.cfm?method=c_about.stats.
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Osborne, E. (1992). A profession that eats its young. Agricultural Education Magazine. 64
(12), 3-4.
Roberts, T. G., & Dyer, J. E. (2004). Inservice needs of traditionally and alternatively
certified agriculture teachers. Journal of Agricultural Education. 45(4), 57-70.
Torres, R. M., Lawver, R. G., Lambert, M. D. (2009). An investigation of job-related stress
among secondary agricultural education teachers in Missouri and North Carolina.
Proceedings of the 2009 American Association for Agricultural Education Research
Conference, Louisville, KY (May 20-22, 2009). 601-614.
United States Department of Education. (2009). Teacher shortage areas nationwide listing
1990-91 thru 2009-10. Office of Postsecondary Education Policy & Budget
Development Staff.
University Interscholastic League. (2010). District alignment and reclassification information
guidelines. Austin, TX. The University of Texas at Austin. Retrieved October, 2010
from: http://www.uiltexas.org/alignments
Walker, W. D., Garton, B. L., Kitchel, T. J. (2004). Job satisfaction and retention of
secondary agriculture teachers. Journal of Agricultural Education. 45(2), 28-38.
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April 20-23, 2011
Changes in Pre-Service Teachers Agricultural Education Teacher Self-Efficacy
Kattlyn J. Wolf, Assistant Professor
University of Idaho
Abstract
The purpose of this study was to describe the teacher self-efficacy of pre-service agriculture
teachers. A researcher created survey instrument with four domains: Classroom, FFA, SAE and
Program Management was utilized. The assessment was administered to all students at the
beginning and end of the semester; Seniors also completed an additional assessment during the
ninth week of school. The pre-service teachers in this study were predominately female, and had
been FFA members and Chapter FFA Officers. Participants reported favorable perceptions of
their teacher preparation program and experiences in teacher-preparation coursework.
Individuals who had been FFA members reported higher levels of teacher self-efficacy on both
assessments, especially in the FFA domain. Seniors preparing for their student teaching
internship reported the greatest increase in teacher self-efficacy between the assessments, while
Juniors reported the least amount of change. Seniors reported positive relationships between
their experiences in the teacher-preparation course work and their Agricultural Education
Teacher Self-Efficacy.
Introduction/Theoretical Framework
“The key to student success is providing an effective teacher in every classroom . . .” (USDE,
2010, p. 3). This is a lofty goal, especially considering “Each fall, more than one hundred
thousand new teachers enter classrooms across America. Some enter with strong preparation,
competent and confident to help their students learn. Many however, are unprepared to meet the
challenges they face (Darling-Hammond & Baratz-Snowden, 2005, p. 1). Agricultural
education, by the complex nature of the program, presents teachers with arguably more difficult
challenges than others entering the teaching profession. Agricultural education also faces a
teacher shortage. In 2007, Kantrovich estimated a teacher deficit of 38.5%. The Pacific
Northwest is not exempt from this shortage. Swan (2009a) found that 27.3% of graduates in the
Pacific Northwest did not enter the teaching profession. The study of teacher self-efficacy may
be a potential solution to the teacher shortage.
The theoretical foundation of this study was grounded in the theory of self-efficacy (Bandura,
1977). Self-efficacy is defined by Bandura (1994) as “people’s beliefs about their capabilities to
produce designated levels of performance that exercise influence over events that affect their
lives” (p. 1). Individuals with a high sense of self-efficacy approach threatening situations with
the belief that they can exercise control over the situation and they can overcome obstacles and
set-backs (Bandura, 1994). The theory of self-efficacy has been applied to teachers and labeled
teacher self-efficacy. Teacher self-efficacy is defined as “…a teacher’s belief that he or she can
reach even difficult students to help them learn... it, [teacher self-efficacy] appears to be one of
the few personal characteristics of teachers correlated with student achievement” (Woolfolk,
2007, p. 334). The suggestion that a teacher’s self-efficacy beliefs are determinants of their
success is a deceptively simple, yet powerful idea (Tschannen-Moran & Woolfolk Hoy, 2001).
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April 20-23, 2011
Teacher self-efficacy is related to plans to stay in the profession of teaching (Evans & Tribble,
1986; Darling-Hammond, Chung, & Frelow, 2002). Therefore, to retain teachers, they must
believe that they are competent in the tasks they are required to perform as agricultural
educators. Assessing this perceived teacher self-efficacy in job-specific tasks will inform teacher
educators about areas in which pre-service and beginning teachers believe they are unable to
affect change. Bandura (1986) has established that efficacy develops partly as a result of past
experiences, specifically four main sources: mastery experiences, physiological and emotional
states, vicarious experiences, and social persuasion (Bandura, 1994). Mastery experiences can
be past experiences with a particular task, or experiences related to the task; for example,
participation in a youth organization.
Knobloch (2006) found that student teachers who had positive perceptions of their teacherpreparation programs were more efficacious at the conclusion of student teaching. Whittington,
McConnell, and Knobloch (2006) found that students’ perceptions of their student teaching
experiences were positively related to teacher self-efficacy. Knobloch (2001) reported that early
field experiences and teaching peers influenced teacher candidates’ sense of teacher selfefficacy, suggesting that students become more efficacious about their teaching because they had
observed and experienced teaching in real settings and had taught their peers.
Wolf, Foster, and Birkenholz (2008) assessed teacher candidates’ level of teacher self-efficacy
and their perceptions of their preparation. Additionally, the researchers investigated the
relationship between teacher self-efficacy and professional experiences during student teaching.
The researchers found that observing young or beginning teachers, a vicarious experience
(Bandura, 1994), was positively related to their sense of efficacy. The amount of feedback
candidates received from their cooperating teacher was also positively related to teacher selfefficacy. The researchers concluded that this feedback enabled teacher candidates to refine and
improve their instructional strategies. The number of class preparations was negatively related to
teacher self-efficacy. This prompted the researchers to recommend that teacher educators
examine the number of classes that candidates are teaching. Bandura (1986) recommended that
self-efficacy is built when an individual is successful at a task. It is possible that teacher
candidates were overloaded, and were not able to experience success in teaching each course
before additional courses were added. The researchers speculated candidates experienced a
“point of diminishing returns” (Wolf, Foster & Birkenholz, p. 26, 2008) when they were
involved in teaching too many courses.
Wolf and Miller (2009) found that beginning teachers were more efficacious in the classroom
domain, when compared with the FFA and SAE domains. Teachers reported the lowest levels of
teacher self-efficacy in the SAE domain. The teachers in this study reported favorable
perceptions of their teacher preparation program and favorable perceptions of their first year of
teaching. Males in this study reported higher levels of teacher self-efficacy than females.
Because of the lower scores in the SAE domain researchers recommended that a greater
emphasis be placed on preparing teachers for SAE related duties during teacher preparation.
Teacher preparation is an important factor in teacher self-efficacy. Knobloch and Whittington
(2002) found that the quality of teacher preparation was associated with student teacher sense of
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April 20-23, 2011
teacher self-efficacy. Ross, Cousins, and Gadalla (1996) found that “feelings of being wellprepared” was associated with teacher self-efficacy. Additionally, Rubecks and Enochs (1991)
found teacher self-efficacy was predicted by university coursework related to future teaching
requirement. Darling-Hammond, Chung, and Frelow (2002) examined the relationship between
perceptions of preparation and teacher self-efficacy and found that ratings of their overall teacher
preparedness were significantly related to their sense of efficacy. Teachers in this study who, “ .
. . felt underprepared were significantly more likely to feel uncertain about how to teach some of
their students and more likely to believe that student’s peers and home environments influence
learning more than teachers do” (p. 294).
Woolfolk Hoy and Hoy stated that “One of the things that makes teacher efficacy [teacher selfefficacy] so powerful is its cyclical nature” (p. 168, 2009). The present study addressed two
components of the model presented ( see Figure 1) by Woolfolk Hoy and Hoy, by assessing
teachers’ assessment of their teaching competence (their sense of efficacy) and investigating
possible personological characteristics that were associated with teacher self-efficacy.




Sources of Efficacy
Mastery Experiences
Emotional states
Verbal persuasion
Social persuasion
Analysis of the
Teaching Task
Cognitive
Processing
Assessment of
Teaching
Competence



Performance

Estimation of
Teacher Sense
of
Efficacy
Consequences of Teacher
Sense of Efficacy
Effort
Persistence
Resilience
Success
Figure 1. A Model of Teacher’s Perceived Efficacy. (Woolfolk Hoy & Hoy 2009)
Although some research in the area of teacher self-efficacy specific to agricultural educators has
been published, no consensus of findings is evident, nor is the literature base extensive. Existing
research has been conducted using general measures of teacher self-efficacy, contradicting the
recommendation from Bandura (2006) to address specific components of a task. “The ‘one
measure fits all’ approach to measuring teacher self-efficacy usually has limited explanatory and
predictive value because most of the items in an all-purpose test may have little or no relevance
to the domain of functioning” (Bandura, p. 307). This research supports the National Research
Agenda for Agricultural Education and Communication, Research Priority Four; Agricultural
Education in Schools: Prepare and provide an abundance of fully qualified and highly motivated
agriscience educators at all levels. Further investigation into pre-service teachers levels of
teacher self-efficacy and the potential sources of teacher self-efficacy will benefit and inform
teacher preparation and teacher professional development in agricultural education.
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April 20-23, 2011
The purpose of this research study was to describe the changes in Agricultural Education
Teacher Self-Efficacy of pre-service teachers. The following research objectives were used to
guide the study.
Objectives of the Study
1. Describe personological characteristics of pre-service agriculture teachers.
2. Describe the perceived levels of teacher self-efficacy of pre-service agriculture teachers.
3. Determine the change in teacher self-efficacy over a semester.
4. Describe the differences in perceived levels of teacher self-efficacy of pre-service
agriculture teachers based on personological characteristics.
5. Describe the relationship among personological characteristics of pre-service agriculture
teachers and their perceived level of teacher self-efficacy.
The population for this descriptive census study (N = 45) was pre-service Agricultural Education
teachers at the University of Idaho in the fall of 2010. Frame and selection error were controlled
by utilizing a current and unduplicated list of students. Data were collected using an instrument
developed by the researcher. The instrument had four domains: Classroom, FFA, SAE and
Program Management. Items specific to agricultural education were incorporated into the
instrument from a variety of sources (Duncan & Ricketts, 2006; Duncan, Ricketts, Peake, &
Uesseler, 2005; Garton & Chung, 1996; Joerger, 2002; Myers, Dyer, & Washburn, 2005;
Roberts & Dyer, 2004). The instrument also contained items from the Instructional Strategies
construct from the Teachers Sense of Efficacy Scale (Tschannen-Moran & Woolfolk Hoy, 2001).
Scaling of the instrument was adapted from the Teachers Sense of Efficacy Scale, using a ninepoint summated rating scale. The scale asked candidates to rate each item following the stem:
“What is your level of capability to . . . <Item?>” on a scale from 1 = No Capability, 3 = Very
Little Capability, 5 = Some Capability, 7 = Quite a Bit of Capability, and 9 = A Great Deal of
Capability. A previous study established the reliability and validity of the instrument (Wolf,
2008). A post-hoc reliability assessment using Cronbach’s alpha internal consistency reliability
coefficient was performed. The reliabilities of the three constructs ranged from 0.83 to .98.
The instrument was administered during the second week of the classes to all students, the 9th
week to Seniors, and during the last week of classes in four different teacher preparation courses.
Non-response error was controlled by a follow up email to participants who did not attend class
on the day the instrument was administered resulting in a final response rate of 100%. The
instrument for the last assessment had personological items. Students’ perceptions of the teacher
preparation program were assessed utilizing a six-point summated rating scale. Seniors
responded to questions related to their experiences in their “Methods” course and their feelings
of preparedness for their student teaching experience on a eight-point summated rating scale.
Data were analyzed using the Statistical Package for the Social Sciences (SPSS v. 18).
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April 20-23, 2011
Findings
The pre-service teachers in this study were all enrolled in the teacher preparation program at the
University of Idaho. Thirty-two females and thirteen males participated in the study. Students
reported their current grade point average at the end of the semester. Seniors reported the
highest current GPA (M = 3.43), juniors (M = 2.88), and sophomores (M = 3.11). Most
participants (66.6%) were FFA members for four years or more and served as a Chapter Officer.
Table 1
Pre-Service Teachers’ FFA Experience (n = 45)
Were you an FFA member?
Did you compete in any State FFA Career Development Events?
Were you a Chapter Officer?
Did you receive you State FFA Degree?
Did you compete in any National FFA Career Development Events?
Did you receive your American FFA Degree?
Were you a State FFA Officer?
Yes %
84.4
80
73.7
60
33.3
24.4
11.1
No %
15.6
20
26.7
40
66.7
75.6
86.7
Students were asked about their perceptions regarding the quality of their education on the
second assessment. These data are presented in Table 2. The item with the highest level of
agreement was “I am pleased with my education in agricultural education to date” (M = 4.86),
and the item with the lowest level of agreement was “My education in College of Education
courses has been high quality” (M = 3.77).
Table 2
Pre-Service Teachers’ Perceptions of Education (n = 35)
Item
Ma
SD
Mo
My education in Agricultural Education courses has been high quality
4.73
1.04
5.00
My education in College of Education courses has been high quality
3.77
1.37
4.00
My high school Agricultural Education program was high quality
4.80
1.45
6.00
I am pleased with my experience in agricultural education to date
4.86
0.93
5.00
a
Note. 1 = Strongly Disagree, 2 = Moderately Disagree, 3 = Mildly Disagree, 4 = Mildly
Agree, 5 = Moderately Agree, 6 = Strongly Agree
Seniors reported favorable perceptions of their pre-service experiences in the fall semester. The
item with the highest level of agreement related to the feedback they received from their
Cooperating Teacher, followed by their level of agreement with the statement “The
microteaching experiences greatly increased my confidence in my teaching.” Students reported
feeling the least prepared to manage a Horticulture or Aquaculture laboratory. Seniors
Somewhat Agreed with the statement that they will be seeking a teaching position following their
student teaching experience.
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April 20-23, 2011
Table 3
Seniors’ Perceptions of their Pre-Service Experiences (n = 10)
Item
Ma
SD
Mo
The microteaching experiences greatly increased my confidence in my teaching 7.20 0.92 7.00
The Cooperating Center teaching experience greatly increased my confidence
in my teaching
6.70 1.34 8.00
My Cooperating Teacher provided me high-quality feedback
7.40 0.70 8.00
I will be seeking a position teaching agricultural education following my
student teaching experience
6.90 0.99 7.00
I feel prepared to teach at my Cooperating Center.
5.80 1.40 7.00
I feel prepared to manage a classroom at my Cooperating Center.
6.10 0.99 6.00
I feel prepared to manage an agricultural mechanics laboratory at my
Cooperating Center.
5.80 1.03 5.0
I feel prepared to manage a Horticulture and/or Aquaculture laboratory at my
cooperating center.
4.80 1.03 4.0
I feel prepared to manage student’s SAE programs at my Cooperating Center.
5.80 0.92 6.0
a
Note. 1 = Very Strongly Disagree, 2 = Strongly Disagree, 3 = Somewhat Disagree, 4 = Slightly
Disagree, 5 = Slightly Agree, 6 = Somewhat Agree, 7 = Strongly Agree, 8= Very Strongly Agree
Male pre-service teachers in this study reported a lower sense of teacher self-efficacy than
females in all areas on the first and last assessment (see Table 3). Females reported the highest
levels of teacher self-efficacy in the SAE domain on assessment two, and the lowest levels in the
classroom domain on assessment one.
Table 4
Agricultural Education Teacher Self-Efficacy by Gender (N = 45)
Female
Male
Assessment 1 Assessment 2 Assessment 1 Assessment 2
Domain
Ma
SD
Ma
SD
Ma
SD
Ma
SD
Classroom
5.73
1.46
5.93
1.22
5.77
1.26
6.60
0.96
FFA
6.21
1.56
6.13
1.54
6.31
1.73
6.99
1.40
SAE
5.86
2.08
5.93
2.09
6.35
1.80
7.08
1.36
Program Management
5.58
1.75
5.86
1.91
5.92
1.87
6.68
1.37
Overall Teacher Self-Efficacy 5.89
1.47
5.98
1.12
6.08
1.44
6.84
1.12
a
Note. 1 = No capability to 9 = A Great Deal of Capability
The assessment was given to all students at the beginning and end of the semester; as well as to
the senior class during the middle; data from the first two assessments is presented in Table 5.
On the second assessment Seniors reported a mean of 6.51 (SD = 0.87) in the classroom domain,
6.42 (SD = 1.39) in the FFA domain, 6.83 (SD = 0.86) in the SAE domain, 6.72 in the Program
Management domain, and 6.58 (SD = 1.00) in overall efficacy. Juniors reported the highest
levels of teacher self-efficacy in most areas on both assessments and in overall efficacy, while
6
April 20-23, 2011
Freshmen reported the lowest levels in most areas and the lowest levels of overall teacher self
efficacy on both assessments.
Table 5
Agricultural Education Teacher Self-Efficacy by Grade Level (N = 45)
Sr
Jr
So
(n = 10)
(n = 14)
(n = 10)
Domain
Ma
SD
Ma
SD
Ma
SD
Classroom 1
5.70
1.13
6.42
1.05
5.73
1.20
Classroom 2
6.61
0.86
6.78
0.83
6.35
1.25
FFA 1
6.03
1.66
6.84
1.81
6.05
1.41
FFA 2
6.73
1.10
7.15
1.56
6.60
1.40
SAE 1
6.47
1.04
7.03
1.81
5.65
1.69
SAE 2
6.79
1.00
7.47
1.47
6.64
1.47
Program Management 1
5.90
2.04
6.36
1.66
5.78
1.44
Program Management 2
6.68
1.01
6.67
1.41
6.64
1.44
Overall Efficacy 1
6.00
1.24
6.68
1.43
5.81
1.28
Overall Efficacy 2
6.70
0.94
7.05
1.18
6.52
1.29
Fr
(n = 11)
Ma
SD
5.00
1.52
5.80
1.18
6.01
1.73
6.36
1.75
5.43
2.40
5.89
2.23
5.11
2.08
5.76
2.18
5.40
1.57
5.98
1.47
Note. a 1 = No capability to 9 = A Great Deal of Capability
1 = Beginning of Fall Semester, 2 = End of Fall Semester
One objective of this study was to determine the changes in teacher self-efficacy over the course
of a single semester (see Table 6). Nearly all students reported an increase in all areas over the
course of the semester. Seniors reported the greatest amount of change in the classroom domain
(0.91) and the least amount of change in the SAE domain (0.32). Juniors reported the least
change in nearly all areas. Sophomores reported the greatest change in the SAE domain (0.98).
Freshmen reported the greatest amount of change in the Classroom domain (0.80), and the least
change in the FFA domain (0.35).
Table 6
Change in Agricultural Education Teacher Self-Efficacy by Grade Level (N = 45)
Sr
Jr
So
(n = 10)
(n = 14)
(n = 10)
Δ*
Δ*
Δ*
Δ*
Δ*
Domain
1 to 2
2 to 3
1 to 3
1 to 3
1 to 3
Classroom
0.81
0.10
0.91
0.36
0.62
FFA
0.39
0.31
0.71
0.31
0.55
SAE
0.36
-0.04
0.32
0.45
0.98
Program Management
0.82
-0.04
0.78
0.31
0.86
Overall Efficacy
0.58
0.11
0.70
0.36
0.71
Note. *1 = first assessment, 2 = second assessment, 3 = third assessment
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April 20-23, 2011
Fr
(n = 11)
Δ*
1 to 3
0.80
0.35
0.46
0.65
0.58
Tables 7-8 present pre-service teachers levels of teacher self-efficacy disaggregated by
participation in FFA activities. Individuals who have participated in FFA activities reported
higher levels of teacher self-efficacy in most domains on both assessments, with the most
pronounced differences during the first week of school. Individuals who had been FFA
members, participated in State CDE’s and were State Officers, higher teacher self-efficacy in all
domains. This difference was most pronounced at the beginning of the semester in the FFA and
SAE domains.
Table 7
Agricultural Education Teacher Self-Efficacy by Participation in FFA Activities During the
First Week of School (n = 45)
Program
Classroom
FFA
SAE
Overall
Mgt
Ma
SD
Ma
SD
Ma
SD
Ma
SD
Ma
SD
Yes
5.86
1.34
6.59
1.51
6.44
1.89
6.09
1.74
6.23
1.40
No
5.22
0.99
4.58
1.50
4.92
1.23
4.37
1.65
4.88
1.09
Yes
5.82
1.39
6.65
1.51
6.45
1.80
6.13
1.70
6.24
1.46
No
5.60
1.06
5.27
1.70
5.54
1.99
4.98
1.94
5.42
1.22
Yes
5.86
1.37
6.81
1.43
6.58
1.83
6.13
1.67
6.33
1.42
No
5.60
1.22
5.49
1.70
5.65
1.86
5.36
1.98
5.56
1.36
Yes
6.75
0.60
7.56
0.35
7.25
0.47
6.88
0.63
7.11
0.12
No
5.72
1.23
6.17
1.69
6.17
1.89
5.77
1.83
5.96
1.40
American Degree
Recipient
Yes
6.23
0.88
6.66
1.48
6.36
1.53
6.05
1.33
6.37
1.19
No
5.61
1.39
6.16
1.72
6.15
2.00
5.75
1.96
5.91
1.50
State CDE
Participant
Yes
5.85
1.34
6.73
1.42
6.62
1.74
6.25
1.63
6.33
1.38
No
5.39
1.12
4.47
1.32
4.54
1.49
4.11
1.55
4.81
0.96
National CDE
Participant
Yes
5.88
1.57
6.72
1.62
6.34
2.28
6.24
2.09
6.26
1.60
No
5.70
1.17
6.06
1.66
6.14
1.69
5.61
1.66
5.90
1.36
FFA Member
Chapter Officer
State Degree
Recipient
State Officer
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April 20-23, 2011
Table 8
Agricultural Education Teacher Self-Efficacy by Participation in FFA Activities During the Last
Week of School (n = 45)
Program
Classroom
FFA
SAE
Overall
Mgt
Ma
SD
Ma
SD
Ma
SD
Ma
SD
Ma
SD
Yes
6.43
1.13
6.90
1.47
6.85
1.77
6.56
1.66
6.70
1.32
No
6.31
0.70
5.87
1.20
6.22
0.74
5.83
0.74
6.12
0.77
Yes
6.36
1.20
6.85
1.40
6.85
1.61
6.60
1.51
6.64
1.31
No
6.55
0.61
6.44
1.69
6.48
1.86
6.02
1.71
6.45
1.16
Yes
6.35
1.15
7.02
1.49
6.96
1.66
6.56
16.1
6.71
1.33
No
6.49
0.96
6.33
1.38
6.43
1.66
6.27
1.52
6.41
1.16
Yes
6.67
1.44
7.68
0.67
7.71
0.74
7.24
0.90
7.26
0.41
No
6.44
1.05
6.66
1.52
6.71
1.66
6.42
1.56
6.57
1.26
Yes
6.57
0.50
6.95
1.39
7.10
1.41
6.64
1.26
6.81
1.0
No
6.35
1.20
6.68
1.51
6.64
1.74
6.38
1.67
6.52
1.34
State CDE
Participant
Yes
6.46
1.13
7.05
1.38
7.04
1.56
6.73
1.49
6.79
1.25
No
6.20
0.80
5.54
1.25
5.57
1.63
5.31
1.43
5.78
0.96
National CDE
Participant
Yes
6.31
1.25
6.95
1.62
6.62
2.24
6.51
2.16
6.58
1.54
No
6.46
1.0
6.64
1.41
6.82
1.32
6.41
1.22
6.59
1.13
FFA Member
Chapter Officer
State Degree
State Officer
American Degree
Personological characteristics were collected to determine the relationship between pre-service
teachers’ levels of teacher self-efficacy and these characteristics. These data are presented in
Table 10. There was a moderate (Davis, 1971) correlation between pre-service teachers
perceptions of their education in AEE courses and program management, and between the FFA
domain and years spent as an FFA member. All other relationships demonstrated a low (Davis,
1971) or negligible association. Grade point average had a negative relationship with all
domains of teacher self-efficacy.
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April 20-23, 2011
Table 9
Relationship Among Personological Characteristics of Pre-Service Teachers and Self-Efficacy
in Agricultural Education During the Last Week of School (n = 34)
Program
Classroom
FFA
SAE
Overall
Mgt
Item
r
r
r
r
r
Current GPA
-.021
-.009
.005
-.043
-.013
Years as an FFA member
.147
.389
.458
.355
.364
My education in AEE courses has been
.313
.316
.342
.309
.352
high quality
My education in College of Education
.132
.134
.123
.092
.137
courses has been high quality
My high School agricultural education
-.044
.166
.080
.132
.081
program was high quality
I am pleased with my experience in
.053
.207
.115
.162
.142
agricultural education to date
Note. .01 to .09 = negligible, .10 to .29 = low, .30 to .49 = moderate, .50 to .69 = substantial,
.70 or higher = very strong (Davis, 1971)
Seniors responded to questions related to their experience during the “Methods” course, the
relationship between their responses and their sense of efficacy are presented in Table 11. There
was a substantial correlation (Davis, 1971) between students’ agreement with the statement “The
microteaching experiences greatly increased my confidence in my teaching” and all domains but
the classroom domain; as well as their feelings of preparedness to teach at their Cooperating
Centers. However, there were low to negligible relationships between students agreement with
the statement “The Cooperating Center teaching experiences greatly increased my confidence in
my teaching” and all domains.
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April 20-23, 2011
Table 10
Relationship Among Personological Characteristics of Seniors and Self-Efficacy in
Agricultural Education During the Last Week of School (n = 10)
Program
Classroom FFA
SAE
Overall
Mgt
Item
r
r
r
r
r
The microteaching experiences greatly
increased my confidence in my
.495
.692
.690
.674
.649
teaching
The Cooperating Center teaching
experience greatly increased my
-.055
.140
.242
.167
.107
confidence in my teaching
My Cooperating Teacher provided me
.500
.574
.656
.546
.589
high-quality feedback
I will be seeking a position teaching
agricultural education following my
.144
.276
.097
.119
.179
student teaching experience
I feel prepared to teach at my Cooperating
.366
.569
.626
.672
.546
Center.
I feel prepared to manage a classroom at
.226
.330
.332
.411
.315
my Cooperating Center.
I feel prepared to manage an agricultural
mechanics laboratory at my
-.066
.143
.112
.208
.075
Cooperating Center.
I feel prepared to manage a Horticulture
and/or Aquaculture laboratory at my
.146
.194
-.053
.060
.107
Cooperating Center.
I feel prepared to manage student’s SAE
.571
.626
.488
.569
.590
programs at my Cooperating Center.
Note. Note. .01 to .09 = negligible, .10 to .29 = low, .30 to .49 = moderate, .50 to .69 =
substantial, .70 or higher = very strong (Davis, 1971)
Conclusions/ Implications/Recommendations
Pre-service teachers in this study were predominately female and were involved in FFA
programs in high school; most had served as Chapter FFA Officers. The majority had also
received their State FFA Degree. Participants reported favorable perceptions of their
experiences in the Agricultural Education Program at the University of Idaho, with slightly less
favorable perceptions of the College of Education courses. Seniors reported overall favorable
perceptions of their pre-service experiences and indicated they felt prepared for their Student
Teaching experience.
The purpose of this study was to describe the teacher self-efficacy of pre-service agriculture
teachers. This study reported pre-service teachers’ perceived self-efficacy in four areas of
agricultural education: classroom, FFA, SAE, and program management at two different points
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April 20-23, 2011
in time. Females reported higher levels of teacher self-efficacy in almost all areas on both
assessments and evidenced a larger change over the semester.
One objective of this study was to determine the changes in Agricultural Education Teacher SelfEfficacy over the course of a semester. Seniors reported the greatest amount of change in nearly
all areas over the course of the semester, most notably the Classroom domain. The seniors were
the only group to complete the assessment during the middle of the semester; the change from
the first assessment to the second assessment was greatest in the Classroom and Program
Management domains. However, less change was reported between the second and third
assessments. Juniors reported the least amount of change over the semester, but higher levels of
teacher self-efficacy on both assessments.
One of the objectives of this study was to describe the differences in teacher self-efficacy based
on personological characteristics. Bandura (1994) stated that self-efficacy is built through
experiences, specifically mastery experiences. The experiences measured in this study were
considered mastery experiences. Individuals who had past FFA experiences reported higher
levels of teacher self-efficacy in nearly all areas; especially on the second assessment. The
differences between individuals who had experiences in FFA and those who did not were the
most pronounced in the FFA and SAE domains, particularly at the time of the first assessment.
Pre-service teachers’ grade point average was negatively related to Agricultural Education
teacher self-efficacy. Years as an FFA member was positively related to the FFA domain, SAE
domain and the Program Management domain. Additionally, positive perceptions of the teacher
preparation program were also positively related to teacher self-efficacy. Teachers’ perceptions
of their high school agricultural education program had a negligible relationship with teacher
self-efficacy. Seniors reported positive relationships between their experiences in their
“Methods” course and Agricultural Education Teacher Self-Efficacy.
The findings in this study raise several questions relative to the Agricultural Education Teacher
self-efficacy of pre-service teachers. Female pre-service teachers in this study outnumbered
males 2 to 1. This finding, in contrast with the number of female teachers in [State] (23%) is
interesting. Are more females attracted to agricultural education in [State] than males? How can
the gender gap be closed? Females reported a greater increase in teacher self-efficacy than males
from the first assessment to the second assessment, and higher levels overall. Why are females
more confident in their abilities? Further research that examines gender differences with regards
to teacher self-efficacy is recommended.
Nearly all students in this study reported increases in self-efficacy over the course of the
semester. Seniors reported the greatest change, as these individuals are preparing to enter their
student teaching experience, and are enrolled in coursework related to that experience, this
finding is encouraging. However, it is important to also note the Seniors perceptions of their
“Methods” course experience. The strong relationships between Seniors perceptions of these
experiences and their teacher self-efficacy indicate that those experiences were effective in
preparing them for their student teaching experience. Further research should more thoroughly
examine the experiences that occur during this semester. As these Seniors transition into teacher
candidates during their student teaching experience, the continual monitoring of their levels of
12
April 20-23, 2011
teacher self-efficacy, as well as the identification of key experiences would further improve the
practices of the teacher education program.
Juniors reported the least amount of change; it will be interesting to see if these students report
the same changes during their senior year. Teacher educators should consider the implication of
these findings as they prepare pre-service teachers for student teaching. FFA membership and
participation was related to teacher self-efficacy in this study. Why? This finding is troubling
for teacher preparation programs, as not all students may be past FFA members. What
remediation is required for non-FFA participants? Should teacher preparation programs require
some FFA experience for admittance to the teacher preparation program? Do other youth
organizations provide similar experiences? The experiences gained in FFA should be carefully
examined to discern their possible impacts on teacher self-efficacy.
Further identification of experiences that build to teacher self-efficacy throughout pre-service
teachers college career is essential to teacher educators as they plan programs of study. Further
research, specifically a longitudinal study of teacher self-efficacy through teacher preparation
and the beginning years of teaching would be appropriate to investigate these questions.
13
April 20-23, 2011
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Description of Agricultural Mechanics Preparation Experience of Arizona
Agricultural Education Teachers
Edward Franklin, University of Arizona
Abstract
The purpose of this study was to describe the agricultural mechanics curriculum
preparation experiences of agriscience teachers in Arizona. A web-based version of an
instrument reported by Pickard and Spiess (2008) was modified for use in this study. A
total of 72 of 94 teachers (77% response rate) responded. A nearly equal number of
female and male teachers responded. The majority of respondents completed a preservice
teacher education program (81%), from the University of Arizona (77%), and reported
from 1 to over 30 years of teaching experience. The majority reported teaching
agricultural mechanics topics in their classes (77%) and averaged 2.5 agricultural
mechanic classes per day. Teachers were asked to review a list of 29 agricultural
mechanics curriculum topics and indicate if they received college-level training on the
topic, their level of preparation, and if they currently teach the topic. Fifty percent and
higher reported receiving training on 23 of 29 topics. The highest rated topics in which
teachers received college training, and taught in their local program were laboratory
safety, and shielded metal arc welding. Though most indicated completed a college
course which included woodworking and construction (82%), slightly more than half
(53%) reported teaching the topic.
Agricultural education instruction affects all three domains of learning: cognitive
domain (knowledge), affective domain (values), and psychomotor domain (skilldevelopment) (McCormick, 1994). Classroom instruction introduces concepts and
principles, targeting the cognitive and affective domains. Laboratory instruction and
practice enhances the development of the psychomotor domain. Having a laboratory
experience to follow-up classroom instruction provides for increased retention of learning
of instructional material (McCormick, 1994) and a deeper appreciation or understanding
of the concepts taught by allowing the student to utilize multiple senses and practice
(Talbert, Vaughn, & Croom, 2005). Classroom and laboratory instruction are
interdependent (Phipps, Osborne, Dyer, and Ball, 2008) teaching tools which attempt to
bring together the “what” and the “how” to accomplish the “why” in agricultural
education. See figure one.
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April 20-23, 2011
Classroom
Instruction
What
Why
How
Laboratory
Learning
Figure 1. The Relationship between Classroom and Laboratory Instruction. From
Handbook on Agricultural Education in Public Schools, by L. J. Phipps, E. W. Osborne,
J. E. Dyer, and A. Ball (2008).
Authors Newcomb, McCracken, Warmbrod, and Whittington (2004) express the
importance of laboratory instruction with the statement, “Without the laboratory, much of
the effectiveness of agricultural instruction is lost” (p. 214). The use of the laboratory in
agricultural education curriculum delivery cannot be undervalued. Agricultural
mechanics instruction is an important part of the high school agricultural education
program across the country (Hubert & Leising, 2000).
Instruction in agricultural mechanics not only reinforces the cognitive and
affective domains of learning introduced in the classroom, but allows the student to
practice psychomotor skill development through application of classroom theory. The
teaching of the technical skills in the agricultural mechanics laboratory is an essential
component in the teaching-learning process in agricultural education (Newcomb et al,
2004). The skills acquired through agricultural mechanic instruction and related-activities
are essential for continual growth and technological development of agriculture (National
FFA Organization, 2008). Phipps and Reynolds (1990) penned of the importance of
agricultural mechanics: “with the increasing mechanization of work, people employed or
self-employed in agriculture cannot be successful unless they possess considerable
mechanical knowledge and skill” (p.4). Phipps et al, (2008) state “Teachers must
constantly update their technical knowledge not only in the subject areas they teach, but
in the latest teaching methodologies and instructional and professional technologies” (p.
368).
The American Association for Agricultural Education (AAAE) published the
document National Standards for Teacher Education of Agriculture. Within the
document Standard 2 states “The design of the teacher education program ensures that
teachers complete a balanced program of general education, technical content, and
pedagogical and professional studies”. Substandard 2c in the same document calls for
agricultural education teacher preparation programs that “are designed so that teacher
candidates attain competencies in basic principles, concepts, and experiential practices in
agricultural science and natural resources related to (B) agricultural and mechanical
systems” (AAAE, 2001).
Previously reported research of secondary agricultural mechanics has addressed
topics such as student teacher anxiety (Foster, 1986), laboratory management needs
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April 20-23, 2011
(Johnson, Schumacher, & Stewart, 1990), the relative importance of specific
programmatic components to local programs (i.e., agriculture mechanics) (Kotrlik &
Druekhammer, 1987) a proposal for curriculum model for agriculture technology
education (Rosencrans & Martin, 1997) and laboratory safety practices (Swan, 1992).
In the last ten years researchers of agricultural mechanics instruction have
examined the technology instruction and university preparation of future high school
teachers (Burris, Robinson & Terry, 2005; Hubert & Leising, 2000; Lawver, Barton,
Akers, Smith, & Fraze, 2003), the perception of technical agriculture preparation
experiences of agriculture mechanic teachers (Ford, Shinn, & Lawver, 2008; Pickard &
Spiess, 2008), and agricultural mechanics laboratory management needs of high school
teachers (Saucier, Schumacher, Funkenbucsh, Terry, & Johnson, 2008; Saucier, Terry, &
Schumacher, 2009).
Burris, Robinson and Terry (2005) sought to answer the question if university
teacher education programs were adequately preparing graduates to teach agricultural
mechanics. The researchers surveyed university teacher preparation faculty to determine
what agricultural mechanic content area was included in their curriculum. Teachereducators were asked to rate perceived level of preparation of students completing their
programs on 53- specific competencies. The researchers grouped the competencies into
nine areas: electricity, metal fabrication, hand/power tools, ag power, building
construction, project planning & materials selection, plumbing, concrete, and machinery
& equipment. Six of nine topics were indicated by over 90 of the survey respondents.
These topics included electricity, metal fabrication, hand & power tools, agriculture
power, building construction and project planning & material selection. The remaining
topics were mentioned by over 80 percent of respondents. Top-rated grouped
competencies were hand/power tools (rated as “prepared”) followed by ag power, metal
fabrication, electricity, building construction, project planning & materials selection,
concrete, plumbing, and machinery equipment (each rated as “somewhat prepared).
Burris et al (2005) recognize that the needs of the local community affect the content of
the program curriculum. The result is a variation in specific agricultural mechanic
competencies presented. Agricultural mechanics is still a valuable part of the secondary
agriculture curriculum. Burris, Robinson and Terry (2005) suggest additional studies be
conducted to determine relevant content of agricultural mechanics in secondary programs
with a focus on identifying emerging competencies
Ford, Shinn, and Lawver (2008) interviewed Texas agricultural science and
technology (AST) instructors to examine which experiences; educational and
professional, industry-related, workshop-related, or a combination was related to success
in teaching agricultural mechanics. The researchers reported the teachers were in
agreement that undergraduate courses did not provide adequate preparation to teach their
current curriculum. Recommendations from the teachers included providing mentoring to
younger teachers from experienced instructors with experience in teaching agricultural
mechanics and the development of three-week workshops for teachers to help teachers
“improve the quality, scope, depth and technical skills in secondary schools” (2008).
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April 20-23, 2011
Researchers Hubert and Leising (2000) asked the question “do students preparing
to teach secondary agricultural education in the next millennium need agricultural
mechanics teaching competencies”? Huber and Leising (2000) attempted to determine if
preservice undergraduate preparation was providing the experience necessary for new
teachers to manage an agricultural mechanics laboratory. They concluded
Lawver, Barton, Akers, Smith, and Fraze (2003) conducted a Delphi study to
determine which agricultural mechanics topics should be included in a university teacher
preparation curriculum. The topic areas with the highest level of agreement and
consensus included metal fabrication, agricultural structures, agriculture power and
machinery, and soil and water management.
Pickard and Spiess (2008) surveyed California agriculture teachers seeking to
determine perceived levels of preparation to teach specific agricultural mechanic
curriculum concepts (Burris et al, 2005). The researchers asked which topics were taught,
examined gender differences in responses, and sought to describe experiences gained
outside of college preparation to teach agriculture mechanic skills. Pickard and Spiess
reported that teachers felt “well/very well prepared” to teach topics as tools (50%), ag
power (36%), machinery (29%), concrete (27%) and building construction (27%).
However, teachers indicated “no preparation” in areas such as small engines (52%),
machinery (45%), plumbing (39%), concrete (38%), project planning (38%), metal
fabrication (34%). A concerning find was 75 percent of respondents said electricity was
taught in their curriculum, yet fewer than 19 percent felt “well/very well prepared” and
23 percent reported “no preparation” to teach to the subject. A similar finding was
observed for project planning; over 80 percent indicated teaching the topic, but 26
percent expressed a level of “well/very well prepared”, and 38 percent reported “no
preparation”. Regarding teachers gaining outside experience, the responses on the nine
curriculum items ranged from 63 percent to 82 percent. No significant differences were
found in differences of perceptions between men and women. Pickard and Spiess
conclude that CA agriculture teachers perceive agriculture mechanics preparation is
declining and an increasing number of teachers are turning to professional development
experiences with industry as a means to become prepared to teach the subject.
Saucier, Schumacher, Funkenbucsh, Terry, and Johnson (2008) studied the
agricultural mechanics laboratory management inservice needs of Missouri agriculture
instructors. The researchers utilized the Borich Needs Assessment Model as a framework
for prioritizing the agriculture mechanics laboratory needs of their study population. A
mean weighted discrepancy score was calculated for each laboratory management
competency. A list of 70 competencies (developed and reported by Johnson and
Schumacher, 1988) served as the survey instrument. Responses were compared to similar
responses from a similar study conducted in 1989. Highest inservice needs were related
to laboratory safety and maintenance and repair of tools and equipment.
This research supports the National Research Agenda for Agricultural Education
and Communication (Osborne, n.d.) Research Priority Five Agricultural Education in
Schools: Prepare and provide an abundance of fully qualified and highly motivated
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April 20-23, 2011
agriscience educators at all levels. The findings of this study will provide teachereducators with information to prepare fully qualified agriscience educators to teach
technical agriculture subjects as agricultural mechanics.
Statement of the Problem
In the state of Arizona, there is one public-funded university with the mission to
prepare and graduate students to become agricultural education teachers. To obtain an
undergraduate degree in teacher education, all students are required to complete a
minimum of 9.0 semester units (three lecture and laboratory courses) in technical
agricultural mechanics. Agricultural education teaching positions in Arizona are filled by
University of Arizona graduates and teachers with other preparation backgrounds.
Professional development workshops focusing on agricultural mechanic curriculum
topics have been presented by the University of Arizona. What is not known is the level
of preparation of agricultural education instructor to teach specific agricultural education
topics, and the extent of instruction of agricultural mechanics topics in the secondary
education program.
The purpose of the study was to examine the preparation of agricultural education
teachers in Arizona to teach agricultural mechanics in their local programs. Specific
objectives were to:
1. Describe the population of agricultural education teachers in Arizona teaching
agricultural mechanics; and
2. Describe collegiate preparation and teaching status of agricultural mechanics
topics; and
3. Determine the level of preparation of agricultural education teachers to teach
specific agricultural mechanics topics.
Method
The population of interest was all agriscience teachers currently employed in
public and charter high school agricultural education programs in Arizona As the size of
the population was deemed accessible (N=94), a census of the population was conducted.
The 2008-9 Arizona Agricultural Education Directory served as the survey frame.
The survey instrument utilized in this study was modified from a version
developed and reported by Pickard and Spiess (2008). For this study, agricultural
mechanics curriculum topics taught during undergraduate courses at the University of
Arizona, and topics specific to agricultural education programs in Arizona were added.
The instrument was composed of five parts. The first part of the instrument sought to
5
April 20-23, 2011
determine the agricultural mechanics curriculum preparation experience of survey
respondents. A list of 29 agricultural mechanics skills was developed using the
agriculture technology management course curriculum and past professional development
topics. To each skill, respondents were asked to mark “yes” or “no” if they took a college
course which included a unit of instruction on the particular skill. The second part of the
instrument asked respondents to indicate their level of preparation in the specific content
area to teach it at their current teaching position. A five-point Likert-type scale was used
(“5” = very well prepared; “4” = well prepared; “3” = somewhat prepared; “2” = not
prepared well; and “1”= no course offered or taken to prepare me”). The third part asked
teachers to mark “yes” or “no” if they currently teach the specific skill in their courses,
and if they received any training in the content area outside of the collegiate setting.
The final part of the instrument sought to obtain demographic information from each
respondent including their gender, a description of their teacher-preparation background,
years of teaching experience, and current agricultural mechanics teaching preparation
experience. A panel of former high school agricultural education teachers with
experience in teaching agricultural mechanics, and university-level agricultural education
faculty reviewed the instrument for face and content validity. Edits were made for
clarification. The survey was uploaded to a commercial survey-hosting server for
distribution.
Each agriscience teacher was sent a personal electronic mail invitation to
participate in the study in August, 2008. A total of 98 email individual messages were
constructed and transmitted using addresses found in the Agricultural Education
Directory. Non-functioning electronic mail addresses were identified from bounce back
messages. These addresses were noted, and if possible a secondary electronic mail
address was identified for the participant. When a valid electronic mail address could not
be located, the subject was deemed “inaccessible” by electronic means. Reminder
electronic mail messages were generated and sent to non-responding participants at the
end of the first and second week. By the end of the second week, 72 respondents (77%
response rate) had participated in the completion of the online survey. A third and fourth
attempt to reach non-responding members of the survey population resulted in no
additional survey completions.
Survey responses were downloaded to Microsoft Excel and recoded for analysis
and entered into SPSS 16.0 for Windows. Since a census of the study population was
conducted, descriptive statistics were employed. Post-hoc reliability analysis yielded
Chronbach’s Alpha of .96 for the construct “Level of preparation to teach each
agriculture mechanics skill”. Frequencies were used to measure categorical and ordinal
data. Means and standard deviations were used to measure scale-type responses. Findings
of this study may be generalized to the study population.
6
April 20-23, 2011
Findings
Objective 1
In order to comprehend the responses of the study population, it was necessary to
examine the background of agricultural education teachers. Teachers were asked to
respond to a series of questions related to their educational background and current status
as a teacher of agricultural education. Responses were received from 72 teachers. Slightly
more than half of the respondents were female (51.4%); most respondents reported
enrollment in community college courses (66.7%), and the majority (80.6%) completed a
preservice teacher education program. The majority of those (77.2%) reported having
received their teacher training at the state land-grant university. Teaching experience
varied. Teachers with 2-5 years of experience (26.4%) and those with 16 years and
greater (26.4%) slightly outnumbered teachers with 6-10 years (22.2%) and first year
teachers (16.7%). The smallest group to report was those in the 11-15 year range (8.3%).
The majority of respondents (77.5%) reported teaching agricultural mechanics within
their courses. The average number of periods of agricultural mechanics taught as either a
stand-alone course, or embedded with an agriscience course was 2.5 per day. Nearly all
respondents (97.2%) report teaching classes other than agricultural mechanics (Table 1).
Table 1
Select Demographic Characteristics of Agricultural Education Instructors (n=72).
Characteristic
f
% Total
Gender
Female
37 51.4 72
Male
35 48.6 72
Completed a Preservice Teacher Education Program
Department of Agricultural Education University of Arizona
Agricultural Education, another institution
A program area other than Agricultural Education
58
44
9
4
80.6
77.2
15.8
7.0
72
57
57
57
Years of Teaching Experience
0-1
2-5
6-10
11-15
16 and greater
12
19
16
6
19
16.7
26.4
22.2
8.3
26.4
Reported teaching agriculture mechanics in agriculture courses
55
77.5
71
Number of class periods of agricultural mechanics per day (avg.)
2.5
Teaching classes other than agricultural mechanics
69
97.2
71
7
April 20-23, 2011
72
Objective 2
The second objective was to determine the level of preparation of teachers to
teach specific agricultural mechanic topics. Respondents were asked to indicate if they
received college instruction on each topic, if they received instruction outside of college
(i.e., attending an industry-workshop), and if they currently teach the topic within an
instructional unit at their local program. Over half of the respondents report having
completed a college course which included 23 of 29 of the agricultural mechanic topics.
Laboratory safety was acknowledged by nearly 90 percent of the teachers. This topic was
currently taught by over 90 percent of the teachers. Five of the topics (shielded metal arc
welding, woodworking & construction, laboratory management, oxy-fuel cutting, and
plumbing) were identified by over 80 percent of the teachers, yet not all topics were
reported to be included in their current curriculum. Of the five presented, woodworking
& construction was taught by just over half of the teachers. Small gas engines was
identified by nearly 70 percent of the teachers as a topic covered in their college course
work, but only 28 percent report teaching the topic. Likewise, topics such as legal land
description, and electric motors, though included in a college course (as reported by
nearly half of the teachers), less than one-quarter indicate teaching a unit of instruction.
The majority of teachers identified four topics that were not included in their college
preparation (less than 25 percent), yet each topic was being taught by more teachers. For
example, only one respondent (1.5%) indicated having any college instruction in
computerized plasma arc cutting, yet 8 teachers (14.3%) report currently teaching the
topic. Similar findings were observed with gas tungsten arc welding (17.9% to 20.3%),
global positioning systems (GPS) (22.4% to 28.8%), and topographic map reading
(23.9% to 32.2%). Table 2 presents all 29 topics and the status of instruction.
Table 2
Completed a College-Level Course Offering Specific Agriculture Mechanics Topics and
Teaching a Unit of Instruction (n=68).
Completed a college-level
Teach a unit of
course including topic
instruction
Topic
f
%
Total
f
%
Total
Laboratory Safety
60
89.6
67
59
92.2
64
Shielded Metal Arc (Stick) Welding
57
83.8
68
48
71.6
67
Woodworking & Construction
55
82.1
67
34
53.1
64
Laboratory Management
54
81.8
66
47
75.8
62
Oxy-fuel Cutting
55
80.9
68
43
66.2
65
Plumbing
54
80.6
67
54
83.1
65
Power Tools
52
78.8
66
50
78.1
64
Tool Identification
52
77.6
67
54
85.7
63
Oxy-fuel Welding
52
76.5
68
33
50.0
66
Electricity/Wiring
51
76.1
67
41
64.1
64
Project Construction
49
75.4
65
46
74.2
62
Cold Metal Work
45
69.2
65
29
46.0
63
Small Gas Engines
47
69.1
68
17
27.9
61
Tool Maintenance
45
68.2
66
17
29.3
58
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April 20-23, 2011
Metal Inert Gas (MIG) Welding
46
67.6
68
Surveying
43
65.2
66
Concrete/Masonry
42
63.6
66
Hot Metal Work
36
55.4
65
Tractor Operation & Maintenance
36
54.5
66
Irrigation Design/Installation
36
52.9
68
Painting/Finishing
33
50.8
65
Plasma Arc Cutting
33
50.0
66
Legal Land Description
33
50.0
58
Electric Motors
32
48.5
66
Hydraulics
18
27.3
66
Topographic Map Reading
16
23.9
67
Global Positioning Systems (GPS)
15
22.4
67
Tungsten Inert Gas (TIG) Welding
12
17.9
67
Computerized Plasma Arc Cutting
1
1.5
67
Note: Frequencies and percentages reported are “Yes” responses.
20
16
22
21
34
46
31
18
13
10
11
19
17
12
8
33.3
26.7
37.3
33.9
55.7
71.9
51.7
30.5
22.4
17.2
19.3
32.2
28.8
20.3
14.3
60
60
59
62
61
64
60
59
58
58
57
59
59
59
56
It is recognized that teachers may receive instruction in agricultural mechanics
from different sources outside of their university program. Teachers may enroll in
community college courses after they receive their degree to acquire skills in specific
topics. Other sources include attending industry-sponsored workshops, or state
department sponsored- inservice activities. However, less than half of the teachers report
receiving instruction on agricultural mechanics topics outside of college. The topic
irrigation design/installation (45.9%) was the highest rated by teachers where training
occurred outside of college. This was followed by shielded metal arc welding (41.9%),
project construction (40.7%), and plumbing (39.3%). The least reported topics were
electric motors (17.2%) and computerized plasma arc cutting (14.3%). See Table 3 for a
listing of the topics and training of respondents.
Table 3
Respondents Reporting Agricultural Mechanic Curriculum Instruction Outside of College
(n=62).
Received training outside of college
Topic
f
%
Total
28
45.9
61
26
41.9
62
24
40.7
59
Plumbing
24
39.3
61
Laboratory Safety
23
38.3
60
Tool Identification
23
38.3
60
Concrete/Masonry
22
37.3
59
Power Tools
22
36.7
60
20
33.3
60
Electricity/Wiring
20
33.3
60
Painting/Finishing
19
32.8
58
9
April 20-23, 2011
19
32.8
Oxy-fuel Cutting
19
31.1
19
31.1
Oxy-fuel Welding
18
29.5
Plasma Arc Cutting
18
30.5
18
31.0
Tool Maintenance
17
29.3
17
28.8
17
28.8
Small Gas Engines
17
27.9
Surveying
16
26.7
13
22.4
12
20.3
Hot Metal Work
12
20.3
Cold Metal Work
12
20.0
Hydraulics
11
19.9
Electric Motors
10
17.2
8
14.3
Note: Frequencies and percentages reported are “Yes” responses.
59
61
61
61
59
58
58
59
59
61
60
58
59
59
60
57
58
56
Objective 3
The third objective was to describe the perceived level of preparation of teachers
to teach the specific topics. A five-point Likert-type scale (5 = Very well prepared; 4 =
Well prepared; 3 = Somewhat prepared; 2 = Not well prepared; and 1 = No course
offered or taken to prepare me) was developed to describe level of preparation. Real
limits were used to describe the level of preparation. Of the 29 agricultural mechanic
topics listed, the teachers identified five topics (17%) they perceived as “well prepared”
to teach. These included laboratory safety (4.26), laboratory management (3.79), tool
identification (3.61), plumbing (3.58), and shielded metal arc welding (3.58). Seventeen
topics (59%) were rated as “somewhat prepared” and were related to construction and
fabrication. Six items (21%) were identified as “not well prepared”. These included:
plasma arc cutting (2.47), electric motors (2.43), topographic map reading (1.95),
tungsten inert gas welding (1.67), global positioning system (GPS) (1.61), and hydraulics
(1.87). One topic (3%) , by its’ rating, described as “No course offered or taken to
prepare me” was computerized plasma arc cutting (1.21). Table 4 presents the findings of
Objective 3.
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April 20-23, 2011
Table 4
Perceived Level of Preparation to Teach Specific Agricultural Mechanic Curriculum
Topics (n=62).
Topic
M
SD
Descriptor
Laboratory Safety
4.26 1.07
Well prepared
3.79 1.29
Well prepared
Tool Identification
3.61 1.33
Well prepared
Plumbing
3.58 1.37
Well prepared
3.58 1.16
Well prepared
3.49 1.19
Somewhat prepared
Power Tools
3.47 1.32
Somewhat prepared
Oxy-fuel Cutting
3.41 1.23
Somewhat prepared
Electricity/Wiring
3.36 1.27
Somewhat prepared
3.30 1.32
Somewhat prepared
Oxy-fuel Welding
3.25 1.22
Somewhat prepared
Tool Maintenance
3.23 1.41
Somewhat prepared
Concrete/Masonry
3.10 1.43
Somewhat prepared
Surveying
3.02 1.23
Somewhat prepared
3.01 1.31
Somewhat prepared
Cold Metal Work
3.00 1.28
Somewhat prepared
Small Gas Engines
2.94 1.53
Somewhat prepared
Painting/Finishing
2.75 1.43
Somewhat prepared
2.73 1.42
Somewhat prepared
2.72 1.53
Somewhat prepared
Hot Metal Work
2.67 1.33
Somewhat prepared
2.52 1.39
Somewhat prepared
Plasma Arc Cutting
2.47 1.42
Not well prepared
Electric Motors
2.43 1.33
Not well prepared
1.95 1.30
Not well prepared
1.67 1.05
Not well prepared
1.61 1.00
Not well prepared
Hydraulics
1.87 1.20
Not well prepared
1.21 0.59 No course offered or taken
to prepare me
Note: Means of 4.51-5.0=Very well prepared, 3.51-4.50=Well prepared, 2.513.50=Somewhat prepared, 1.51-2.50=Not well prepared, 1-1.50=No course offered or
taken to prepare me.
Conclusions/Implications/Recommendations
This study sought to describe the agricultural mechanic preparation of experiences
of Arizona agricultural education teachers. A list of competencies drawn from the
agricultural mechanic curriculum for the preservice program of the teacher-training
institution in Arizona, and most the requested inservice topic (automated plasma or
computerized plasma cutting systems) was used as the basis of the study.
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April 20-23, 2011
Agricultural education teachers participating in this study were likely to have
completed their preservice teacher education program, and completed technical
agricultural mechanics course work that included the majority of the agricultural
mechanics topics listed in this study. Agricultural mechanics topics were taught by the
majority of agricultural education teachers in Arizona The topics were either embedded
in agriscience courses, or offered in stand-alone agricultural mechanic courses.
Agricultural education teachers in Arizona reported to be teaching, and well
prepared to teach agricultural mechanic topics as laboratory safety and laboratory
management; two topics which were found to be high priority inservice items in similar
studies (Hubert & Leising, 2000; Johnson, Schumacher, & Stewart, 1990). A study
conducted in Arizona (Miller, 1991) examined the level of compliance with select safety
competencies of a sample of agricultural mechanic laboratories. The researcher found an
overall neglect of safety practices. The 1990 study should be replicated to determine if
laboratory safety practices in Arizona have improved. The findings of the 1990 study
may have resulted in an increase in the emphasis of safety instruction and laboratory
management practices in the university curriculum.
Additional topics which teachers’ reported were well prepared to teach included
plumbing and shielded metal arc welding. For both topics teachers reported receiving
additional training outside of the university setting. This would contribute to a higher
level of preparation to teach the subjects.
Another observation noted was that not all topics with high percentage of college
course completion were necessarily taught at the high school level. Woodworking and
construction was a topic that was presented or covered in a university course as reported
by 84 percent of the respondents. However, slightly more than half (53%) were reported
to actually teaching the subject. There may be several reasons an instructor does not
teach a specific topic. Duplication of curriculum topics by multiple programs in the same
school may prevent teachers from offering the topic. For example, a school with a
comprehensive Career and Technical Education program may have a woodworking and
construction program onsite and may not support two programs teaching similar topics.
All curriculum topics listed as “not well prepared”, and “no course offered or
taken” should be examined further to determine if (a) the topic is relevant to
contemporary secondary agricultural mechanics program; (b) if the topic is appropriate
for the local community; and (c) if the topics are necessary for employment in today’s
agriculture industry. Computerized plasma cutting systems was the lone topic to receive
the descriptor of “no course offered or taken”; yet was reported to be taught be a small
number of respondents (14%). This may suggest that a growing number of high school
programs are giving attention to the technology yet teachers are not receiving training.
Future research should be conducted to identify specific agricultural mechanic
inservice needs of Arizona teachers along with the preferred method of receiving the
topic. Additionally, research should seek to answer the questions of (1) how essential are
12
April 20-23, 2011
the agricultural mechanics topics presented in university teacher preparation programs to
today’s agriculture technology industries? (2) Are the topics taught to future classroom
teachers relevant? And (3) do university preparation programs need to change and update
the curriculum to better prepare the next generation of high school agriscience program
graduates?
13
April 20-23, 2011
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McCormick, F.G. (1994). The power of positive teaching. Malabar, FL: Krieger
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April 20-23, 2011
Determining the Effect of a Science-Enhanced Curriculum Taught in an Animal Science or
Horticulture Course on Student Science Achievement: A Causal Comparative Study
J. Chris Haynes, J. Shane Robinson, M. Craig Edwards, James P. Key
Abstract
The National Commission on Excellence in Education identified that according to the general
public, serious problems in our educational system persist. The academic skills of today’s
teenagers are diminishing and is a cause for concern. One of the academic areas in need of
improvement is science. The purpose of this causal comparative study was to determine the effect
that a science-enhanced, curriculum would have on students’ science achievement. The
population for this study to use the curriculum consisted of students selected by Agricultural
Education Division staff whose secondary agricultural education instructors held a science
credential in Oklahoma. Additionally, 10 equally credentialed instructors formed a purposeful
comparison group and were selected according to specific variables (e.g., similarity of students’
SES status) for equivalency purposes. The findings of this study revealed that a statistically
significant difference in student science achievement did not exist as a result of the treatment.
However, small practical differences were detected between the groups, as student performance
in the treatment group were more than two and one-half points greater than the means of
students’ performance scores in the comparison group. Recommendations point to the need for
replication of the study over one school year.
Introduction and Conceptual Framework
The academic skills of today’s teenagers are diminishing, and a cause for concern exists among
both state and national officials (Cavanagh, 2004). One of the academic areas in need of
improvement is science (Dickinson & Jackson, 2008; National Center for Education Statistics,
2005; Provasnik, Gonzales, & Miller, 2009). The National Commission on Excellence in
Education identified that a “. . . widespread public perception that something is seriously remiss
in our educational system” (NCEE, 1983, p. 1) exists. Additionally, in the report, A Nation at
Risk: The Imperative for Educational Reform, it was stated that, “. . . The educational
foundations of our society are being eroded by a rising tide of mediocrity” (p. 5). Lloyd (1992)
posited that as a result of three decades of educational reports, evidence exists to support the
need for educational change.
Reports on the success of students from across the globe in comparison to the achievements of
those in the United States indicate that American students are falling behind in science
achievement when compared to other countries (National Center for Education Statistics, 2005;
Provasnik et al., 2009). Further, it appears as though progress in science achievement of
American students has been stagnating. As of 2007, the United States was ranked ninth out of 47
countries that participated in the Trends in International Mathematics and Science Study
(TIMSS). Countries out-ranking American students in science achievement scores were
Singapore, Chinese Taipei, Japan, Korea, England, Hungary, the Czech Republic, Slovenia, and
the Russian Federation (National Center for Education Statistics, 2005).
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April 20-23, 2011
Cavanagh (2004) noted that, according to the American College Testing (ACT) program, 78% of
students who took a college entrance examination were deficient in the areas of mathematics,
science, and English. Thus, it was determined that these students were ill-prepared for collegelevel coursework, justifying the need for improvements at the secondary level. Further, it was
noted in the latest Program for International Student Assessment (PISA) that, “U.S. 15-year-olds
are not able to apply scientific knowledge and skills to real world tasks as well as their peers . . .”
(Provasnik et al., 2009, p. 45).
Provasnik et al. (2009) compared the average science scale scores of students in the United
States to international students in the areas of reading, mathematics, and science. It was
determined that Oklahoma ranked 28th in the nation out of the 45 states that reported science
achievement scores. This figure is discouraging and serves as an indicator of the lack of
preparedness of students for higher education and the real world.
Secondary agricultural education exists to prepare people for college and careers (Roberts &
Ball, 2009). Because it has long been lauded as the world’s oldest science (Ricketts, Duncan, &
Peake, 2006), agricultural education strives to help students understand scientific principles and
concepts in the context of agriculture better (Thompson & Balschweid, 2000). As such,
agricultural education could serve as an effective medium to convey scientific terminology,
principles, and those concepts that are inherent to botany and zoology (Parr & Edwards, 2004).
Because agricultural education holds the potential to effectively aid students in understanding
science better through the context of agriculture, curricula developed toward this end should be
made available in the secondary classroom. One such curriculum is available through the Center
for Agricultural and Environmental Research and Training (CAERT). CAERT provides
agriculturally-based, science-enhanced materials available for use in agricultural and
environmental instructional areas at the secondary level (CAERT, 2010a). Specializing in
activities that are collaborative by nature, students of agricultural education are provided a
curriculum that is intended to allow them to be more actively involved and engaged in the
learning process (CAERT, 2010a).
Conceptually, this study was undergirded by the constructivism and brain-based learning (BBL)
theories whereby people learn in authentic environments by connecting their learning to prior
knowledge (Doolittle & Camp, 1999). The constructivist theory, according to Brown (1998),
relies on strategies of implementation such as, “student-centered teaching, project-oriented
instruction, problem-based learning, and contextual teaching and learning (p. 3).”
Specifically, Caine and Caine (1995) stated that the brain is a parallel processor, capable of
performing functions and activities simultaneously making the most of learning. The brain
factors “thoughts, emotions, imagination, and predispositions” (Caine & Caine, 1990, p. 66) in a
seamless fashion; therefore, the concept of contextual teaching and learning is promising (Parr,
Edwards, & Leising, 2006). Connections must be made in education between the acquisition of
knowledge and its practical application in the “real world” (Parr, Edwards, & Leising, 2009).
Regardless, for effective construction to occur, learning must be meaningful and relevant to
students (Caine & Caine, 1989). As a result, educators should take advantage of the academic
possibilities of brain-based learning and develop lessons and curriculum suitable for this
modality of learning (Caine & Caine, 1995).
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April 20-23, 2011
These contextual experiences are unique, but contain relevant points of continuity that transfer
from each distinctive learning experience (Caine & Caine, 1994). Specifically, it is evident that
the primary goal is for educators as well as learners to move away from the concept of
memorization and to embrace meaningful learning (Bellah et al., 2007). For this to occur, the
brain must be relaxed, immersed, and active (Caine & Caine, 1989).
High stakes tests have placed increased requirements on schools to raise students’ test scores in
science. Moreover, the ever-increasing demand for workers who are scientifically literate and
capable of applying their understanding of science in the workplace continues to be an escalating
imperative. Agricultural education, at the secondary level, including animal science and
horticulture curriculums, is based inherently on fundamental science principles and concepts.
However, little empirical evidence exists that demonstrates whether teaching a science-enhanced
curriculum in the context of animal or plant science courses would affect student achievement in
science positively.
Purpose, Objectives, and Research Hypothesis
The purpose of this study was to determine if a science-enhanced curriculum (i.e., CAERT)
taught in a secondary level animal science or horticulture course would improve students’
understanding of selected scientific principles significantly, when compared to students who
were instructed using a traditional curriculum. The following research questions guided this
study.
1. What were the personal characteristics (i.e., gender, age, grade classification, Biology I
End of Instruction score, race/ethnicity, and number of agricultural education courses
taken) of students enrolled in selected animal science or horticulture courses in Oklahoma
during spring semester 2010?
2. What was the effect of a science-enhanced (i.e., CAERT) curriculum on students’ science
achievement, as determined by a science proficiency examination?
Ho1: The science achievement of students who received the science-enhanced CAERT
curriculum in animal science or horticulture will not differ significantly (i.e., p < .05) from those
students who were taught the traditional animal science or horticulture curriculum, as measured
by the TerraNova3 science achievement examination (Ho: µ1treatment group = µ2comparison group).
Methodology
The population for this study consisted of students whose secondary agricultural education
instructors held a science credential in Oklahoma during the 2008-2009 school year. The
purposeful sample consisted of 10 treatment groups including students whose teachers were
selected by Agricultural Education Division staff of the ODCTE to use the science-enhanced
CAERT curriculum developed for the instruction of animal science and horticulture courses
during the 2009-2010 school year. In addition, students of 10 different instructors formed a
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April 20-23, 2011
purposeful comparison group. These teachers also held a science credential and were selected
according to specific school and student data obtained from the 2008-2009 Computerized
Enrollment System for Instructors (CESI) report. The CESI report is used by the ODCTE’s,
Information Management Division to collect selected characteristics information of Oklahoma
secondary agricultural education programs and their students. Therefore, schools that “matched”
the treatment group based on review of established criteria were selected to provide an
appropriate counterfactual group (Creswell, 2008) for the comparison of results.
The criteria used in this study were established and recommended by the National Research
Center for Career and Technical Education (NRCCTE), who also provided partial funding for the
study. The criteria considered for selection of the counterfactual group included agricultural
education instructors that held an instructional certification in science at the time of the study, as
well as academic performance index (API) scores of their schools, and socioeconomic status
(SES) of the student participants. Random sampling was used to select students to take the
science examination. The instructors’ classrooms served as the study’s “units of analysis” for
purposes of comparison.
The design of the study was ex post facto, causal comparative because no random assignment of
the treatment group occurred (Ary, Jacobs & Razavieh, 2002). The treatment group was “predetermined” through selection of instructors by ODCTE staff, i.e., agricultural education
teachers who received access to the CAERT curriculum. The curriculum was designed to
explicate and reinforce scientific principles through the instruction of select agricultural
education courses, including modules supported by downloadable lesson plans, aligned learning
standards, summary reports, PowerPoint® files, and E-Units (K. Murray, personal
communication, October 1, 2009). E-Units are online student text resources that are designed to
reinforce the lesson plans that were a part of the CAERT science-enhanced curriculum (D.
Pentony, personal communication, December 6, 2010).
The CAERT curriculum was selected for use because it was developed according to standards
for agricultural education in Oklahoma, was acceptable for science credit for college entrance
purposes, and consisted of an online delivery method. As a result of the state alignment, the
animal science curriculum included 28 units with 160 instructional lessons, and the horticulture
curriculum included 29 units with 148 lessons (CAERT, 2010b). The unique purpose of CAERT
is that it is a science-enhanced curriculum not otherwise offered by curriculum providers for use
in Oklahoma (K. Murray, personal communication, October 1, 2009).
The treatment group teachers were provided access to the CAERT curriculum via passwords and
user names in summer 2009. These teachers were instructed by ODCTE state staff members to
become familiar with the modules pertaining to animal science and horticulture prior to the
beginning of the up-coming fall semester. Additionally, this group of teachers was brought onto
the ODCTE campus for a one-half day training seminar during September 2009 for an overview
of the curriculum (i.e., the functions of the curriculum and how to use its teaching resources).
For the purpose of testing this study’s intervention (i.e., the CAERT curriculum), a purposeful
comparison group was selected from the same list of agricultural education teachers who had
achieved science certification in Oklahoma (N = 40). This group was instructed to teach their
courses (i.e., animal science or horticulture) as they had in the past.
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April 20-23, 2011
To determine equivalency of the treatment and comparison groups, student performance was
compared on the Oklahoma Department of Education’s End of Instruction (EOI) examination in
science. In addition, school district’s academic performance index and accountability data (API),
and the schools’ percentage of low income clientele served by the free and reduced lunch
program (SES) were compared.
The Oklahoma Department of Education’s EOI examination in science is a part of a larger
statewide testing program known as the Oklahoma School Testing Program (OSTP) (Oklahoma
State Department of Education, 2010a). Students completing an area of instruction are expected
to pass the corresponding standardized assessment. EOI examinations are designed to assess a
student’s level of competency relative to the Priority Academic Student Skills (PASS), which are
Oklahoma-based content standards (Oklahoma State Department of Education, 2010b).
Evaluation of student competency level in Biology involved the use of core curriculum test
scores for Biology in Oklahoma. These core curriculum tests for students in Oklahoma are
categorized in accordance with student ability level as established by local school administration
and admission, review, and dismissal (ARD) meetings. The two types of core curriculum tests
used to measure student science achievement include the Biology I End of Instruction test, which
is administered to the general school population, and the Oklahoma Modified Alternate
Assessment Program (OMAAP) test, which is administered to those students qualifying for
modified testing as a result of local ARD meetings.
Four performance levels exist to classify student achievement. For the regular test administration
(i.e., EOI), performance levels are divided into “advanced” (755 – 999), “satisfactory” (691 –
774), “limited knowledge” (627 – 690), and “unsatisfactory” (440 – 626). The alternate test
administration (OMAAP) is divided into four performance levels. They consist of “advanced”
(265 – 350), “satisfactory” (250 – 264), “limited knowledge” (233 – 249), and “unsatisfactory”
(100 – 232) (Oklahoma State Department of Education, 2010c). EOI categorical scores were
coded as 1 = “unsatisfactory,” 2 = “limited knowledge,” 3 = “satisfactory,” and 4 = “advanced”
for comparison purposes between the regular and alternate test administrations (Oklahoma State
Department of Education, 2010a).
The Academic Performance Index (API) for Oklahoma was developed based on the need to
compare school performance to meet requirements established by Oklahoma law, as well as
legislation pursuant to Public Law 107-110, commonly referred to as No Child Left Behind
(Oklahoma State Department of Education, 2010c). API scores range from 0 to 1500, with the
most recent reported state average being 1279 (Oklahoma State Department of Education,
2010c). Components of a school’s API include EOI scores, Academic Excellence as measured
by students’ participation in the ACT college entrance examination, remediation rates for college
students in reading and mathematics, and school completion, as determined by student
attendance coupled with graduation and dropout rates (2010c). To ensure equivalency of the
treatment and comparison groups, schools were compared on the basis of EOI scores, API, and
socioeconomic status (SES).
When comparing these variables for equivalency, the treatment group had an EOI group mean
score of 2.67 (2 = “limited knowledge”) (SD = 1.12). The mean score for the comparison group
was 2.88 (2 = “limited knowledge”) (SD = .93). The treatment group had an API group mean
score of 1387.00 (SD = 57.42); the mean score for the comparison group was 1295.86 (SD =
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April 20-23, 2011
74.40). The treatment group had a SES group mean score of 44.85 (SD = 13.94). The comparison
group had a mean score of 43.53 (SD = 9.40) for SES. An independent samples t-test comparison
of the treatment and comparison groups did not reveal a statistically significant difference in
student science knowledge (p = .580) prior to the treatment at an a priori alpha level of .05
(Table 1).
Independent samples t-tests was used to compare the treatment and comparison group
participants on the EOI, API, and SES variables. It was revealed that a statistically significant
difference (Table 1) in API scores existed between the two groups (p = .045) at an a priori alpha
level of .05. Therefore, the reader is cautioned on making generalizations beyond the sample
examined in the study.
Table 1
Treatment and Comparison Group Equivalency According to A Comparison of
EOI, API, and Socio-Economic Status Scores
Groups
Min. & Max.
M
SD
t-value
p-value
EOIa
EOIb
1–4
APIa
APIb
SESa
SESb
a
2.67
2.88
1.12
.93
-.561
.579
0 – 1500
1387.00
1295.86
57.42
74.40
2.290
.045*
0 – 100%
44.85
43.53
13.94
9.40
.197
.848
= Treatment; b = Comparison; *p < .05
School district testing liaisons arranged for and proctored the science examination. To determine
the effect that a science-enhanced CAERT curriculum had on students’ science achievement, a
science proficiency examination was used. The TerraNova3 Form G assessment series
examination, designed and developed by CTB/McGraw-Hill, (a subsidiary of The McGraw-Hill
Companies, Inc) was the examination used in this study.
The examination consisted of normed sections that are designed to test student competencies in
reading, language, mathematics, social studies, and science (CTB/McGraw-Hill LLC, 2008). “A
normed section is a subset of TerraNova Third Edition for which scores from a nationally
representative norm group are available” (CTB/McGraw-Hill LLC, 2008, p. 1). The normed
section for science consists of 40 multiple choice questions designed to assess student
competence in science. Students were provided with four answers for each multiple choice
question from which to determine the correct answer.
The NRCCTE agreed to provide science examinations and their scoring for 80 students in the
study (i.e., four to five students per classroom, treatment and counterfactual). An online
calculator was used to estimate the appropriate sample size needed for this study (Soper, 2010).
It was found while using three covariates for prediction, that 76 participants were needed to
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April 20-23, 2011
accommodate an alpha level of .05, with an anticipated effect size of .15, and a desired power
level of .80. For practical testing purposes, 80 treatment and comparison students were randomly
chosen from the 20 classrooms in the study to participate in taking the science examination. This
allowed the researcher to randomly select four to five students per classroom to achieve the
appropriate sample size for the study. In all, 80 students were selected randomly to ensure a
strong power analysis and effect size for the study (J. Stone, personal communication, December
3, 2009). Power is determined typically by sample size (Keppel, 1991) and is defined as, “the
probability of correctly rejecting a false null hypothesis” (Shavelson, 1996, p. 314). Therefore,
one means to increase power is to increase sample size. As power increases, so does the
magnitude of the effect, or effect size (Shavelson). “Effect size is the discrepancy between the
null hypothesis and the alternative hypothesis of interest” (Shavelson, 1996, p. 317).
Statistical analysis for the study was completed with the Predictive Analytics Software (PASW)
18.0 and Microsoft Excel 2007. To assess research question one, students were asked to identify
characteristics pertaining to their gender, age, grade classification, and race/ethnicity. To
summarize trends and tendencies relating to the personal characteristics data, descriptive
statistics (i.e., mean, median, mode, frequency, and percentages) were computed. To assess
research question two, an independent samples t-test was used. Ary, Jacobs, and Razavieh (2002)
identified that a t-test for independent samples serves as an ideal statistical procedure for
determining statistically significant differences between groups.
Effect sizes were also calculated to determine what practical effect the treatment had on the posttreatment measures of the study (i.e., animal science and horticulture agricultural competency
examinations). The effect size was calculated per Cohen’s (1988) procedure. According to
Cohen, effect size is calculated and compared to three benchmark standards: “small” effect size
(d = .20), “medium” effect size (d = .50), and “large” effect size (d = .80). However, research by
Thompson (2002) indicated that adherence to this standard may be too stringent and that the
effect itself is determined by what has been studied. For example, large effect sizes can be
considered trivial when applied to outcomes that are trivial (Trusty, Thompson, & Petrocelli,
2004). So, the benchmark standards as identified by Cohen to interpret effect size for selected
results of this study (as calculated by Cohen’s formula) were expanded and compared to the
following standard proffered by Thalheimer and Cook (2002) (Table 2).
Table 2
Relative Size of Cohen’s d According to Thalheimer and Cook (2002)
Effect Size Classification
Relative Size
Negligible Effect
Small Effect
Medium Effect
Large Effect
Very Large Effect
Huge Effect
> = - 0.15 and < .15
> = .15 and < .40
> = .40 and < .75
> = .75 and < 1.10
> = 1.10 and < 1.45
> 1.45
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April 20-23, 2011
Using Thalheimer and Cook (2002), the relative size of a “negligible” effect must be greater than
or equal to – 0.15 and less than .15. To be classified as having had a “small” effect, the relative
size must be greater than or equal to .15 but below .40. A “medium” effect classification must be
greater than or equal to .40 but less than .75 in relative size. Those effect sizes that are
considered to be “large” must have a relative size of greater than or equal to .75 but less than
1.10. To have an effect size classified as “very large,” the relative size must be greater than or
equal to 1.10 but less than 1.45. Finally, to have an effect size considered to be “huge,” the
relative size must be greater than 1.45.
Agricultural teachers and their students from 20 secondary agricultural education programs in the
state of Oklahoma served as the subjects for this study and provided the data described in the
findings section. However, mortality occurred during the study and affected the final sample
size. Mortality is “a potential threat to internal validity in an experiment when individuals drop
out during the experiment for any number of reasons” (Creswell, 2008, p. 642).
Findings/Results
Research question one sought to determine the personal characteristics (i.e., gender, age, grade
classification, end of instruction score (EOI), number of agricultural science courses taken and
race/ethnicity) of students who were enrolled in the targeted Oklahoma animal science or
horticulture courses involved in the study (N = 80). The students who were involved in the study
were asked for their personal characteristics information in conjunction with their post-test
administrations. A total of 69 students completed the questionnaire (treatment n = 29;
comparison n = 40) administered during the post treatment testing process.
The treatment group students included 13 males (45%) and 16 females (55%) (Table 3). None of
the students in the treatment group were 14 years of age. One respondent was 15 (3%), nine
respondents were 16 (31%), six (21%) respondents were 17, and 13 (45%) respondents were 18
years of age or older.
Regarding race/ethnicity of those who responded, 24 respondents (83%) self-selected their
classification as White/Caucasian. None of the students reported that they were AfricanAmerican or Asian. Four (14%) students reported that they were American Indian/Alaskan
Native/Pacific Islander, and one (3%) student selected his/her ethnicity as “other” (Table 3).
No respondents from the treatment group represented the ninth grade. Eleven of the respondents
(38%) were tenth graders, four of the respondents (14%) were eleventh graders, and the other 14
students (48%) were twelfth graders (Table 3).
The comparison group students consisted of 18 (45%) males and 22 (55%) females (Table 3).
One of the respondents (3%) was 14 years of age, and five (13%) were 15 years of age. Fifteen
(38%) respondents were 16 years of age, 11(28%) were 17 years of age, and eight (20%) were 18
years of age or older (Table 3).
As for race/ethnicity, 34 (85%) students classified themselves as White/Caucasian, five (13%)
identified their race/ethnicity as being American Indian/Alaskan Native/Pacific Islander, and one
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April 20-23, 2011
respondent (3%) selected the “other” classification. None of the students identified that they
were African-American or Asian (Table 3).
None of the comparison group students were eighth graders. Rather, the students were
distributed evenly across the remaining grade classification levels: six respondents (15%) were
ninth graders, 17 (43%) were tenth graders, seven (18%) were eleventh graders, and 10 (25%)
were twelfth graders (Table 3).
Table 3
Selected Personal Characteristics of Treatment (n= 29) and Comparison (n= 40) Group
Students
Treatment
Comparison
Variable
f
%
f
%
Gender
Male
Female
Age
14
15
16
13
16
44.8
55.2
18
22
45.0
55.0
0
1
9
0.0
3.4
31.0
1
5
15
2.5
12.5
37.5
6
13
20.7
44.8
11
8
27.5
20.0
24
4
1
82.8
13.8
3.4
34
5
1
85.0
12.5
2.5
9th
0
0.0
6
15.0
10th
11th
12th
11
4
14
37.9
13.8
48.2
17
7
10
42.5
17.5
25.0
17
18 years or older
Race/Ethnicity
White/Caucasian
American Indian/Alaskan Native/Pacific Islander
Other
Grade Classification
Research question number two sought to determine the effect that a science-enhanced CAERT
curriculum had on students’ science achievement, as determined by the TerraNova3 science
proficiency examination. The science portion of the examination was administered after the
treatment (i.e., teaching of the CAERT science-enhanced curriculum) to assess and compare the
science achievement of the treatment and comparison group students. Data were analyzed and
converted to percentages (0 – 100) from raw data (0 – 40) for purposes of analysis using the
following formula:
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April 20-23, 2011
Science-Enhanced Examination Raw Score/Total Raw Score X 100 = % Score
The treatment group students (n = 29) who took the science-enhanced examination had a group
mean score of 55.86 with a standard deviation of 16.55 (Table 4). The comparison group
students (n = 40) had a group mean score of 53.31 with a standard deviation of 16.01. An
independent samples t-test comparison of the treatment and comparison groups did not reveal a
statistically significant difference in science achievement as a result of the treatment (t = .64; p =
.522) at an a priori alpha level of .05. Further, the effect size, calculated according to Thalheimer
and Cook (2002), resulted in a “small” effect (d = .16) (Table 4). As such, the null hypothesis
(Ho1) was accepted, indicating that the science-enhanced CAERT curriculum did not have a
statistically significant effect (p < .05) on students’ science achievement.
Table 4
Science-Achievement Examination Scores of Treatment and Comparison Groups
TerraNova3Examination Min. & Max.
f
M
SD
t-value
p-value
Treatment
Comparison
0-100
29
40
55.86
53.31
16.55
16.01
.644
.522a
p < .05; aEffect size = “Small” (.16 per Cohen’s d; Thalheimer & Cook, 2002)
Limitations
Certain conditions and variables important to this study were outside of the control of the
researcher. For example, treatment teachers were selected purposefully by _DCTE state staff
which affected generalizability of the study due to non-randomization of the treatment teachers.
Further, multiple attempts were made at collecting EOI data for those students who participated
in the study. In Oklahoma, each school district “houses” its own student database (i.e., EOI
results). As such, some schools were reluctant to release those data for the purpose of the study.
Additionally, comparison of the schools by API scores found that the treatment group schools
were statistically significant different indicating a higher degree of aptitude overall. Finally, no
incentives were provided for the teachers. Unfortunately, some teachers chose not to use the
curriculum in its entirety or test their students accordingly.
Conclusions
The purpose of this study was to determine if a science-enhanced curriculum (i.e., CAERT)
taught in a secondary level animal science or horticulture course would improve students’
understanding of selected scientific principles significantly when compared to students who were
instructed using a traditional curriculum. This study found that a majority of those students who
participated were female. In fact, 55% of the students in the treatment and comparison groups
were female. Further, in terms of Race/Ethnicity, the category representing the majority of both
groups (treatment and comparison) was White/Caucasian. Finally, most students were 16 years
of age or older and belonged to the sophomore and senior classes primarily. This study found
that the use of a science-enhanced CAERT curriculum did not result in a statistically significant
increase (p < .05) in student performance as determined by the TerraNova3 science proficiency
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April 20-23, 2011
examination. Therefore, the null hypothesis was not rejected. However, small practical
differences were detected between the groups, as student performance score means in the
treatment group were more than two and one-half points higher than the means of students’
performance scores in the comparison group. Although not statistically significant, these results
are similar to findings reported by Roegge and Russell (1990). The findings also suggest that
students can learn content better when it is embedded in a familiar context (Caine & Caine,
1995; Roberts & Ball, 2009).
Recommendations for Research
Although the findings of this study did not indicate a statistically significant difference in science
achievement for the treatment group students, the intervention (i.e., the science-enhanced,
CAERT curriculum) may have potential in this area. However, future research is needed.
Because the treatment sample was pre-determined by _DCTE staff, the generalizability of this
study suffers. So, this study should be replicated using a true experimental design in which
teachers are randomly selected in an effort to generalize any future findings more broadly.
A future investigation should occur with a different sample of teachers to determine if the
science-enhanced CAERT curriculum was the determining factor in the outcome of the research
that was conducted, or if it was a result of teacher effect. To answer this question, a hierarchical
linear modeling (HLM) analysis could be conducted.
This study lacked prolonged, sustained professional development regarding pedagogy needed to
teach science content effectively (e.g., an inquiry-based teaching approach). Therefore, from a
pedagogical perspective (Brazen & Clark, 2005), future research should determine if a studentcentered approach (e.g., inquiry-based teaching and learning) has an effect on students’ ability to
learn science in the context of agriculture when compared to a teacher-centered approach.
Recommendations for Practice
The science achievement of students who were exposed to the study’s treatment (i.e., the
science-enhanced, CAERT curriculum) yielded promising results. The integration of a scienceenhanced curriculum into a program of agricultural education did increase the science
achievement of students. Edling (1993) stated that, “Learning is greatly strengthened if concrete
examples or situations familiar to the student can be utilized in the learning process” (Contextual
learning section, para. 2). Put simply, students are capable of learning better when information is
presented to them in a way that it relates to their personal experiences. As a result of the findings
of this study and others, (e.g., Roegge & Russell, 1990; Parr et al., 2006; Young, Edwards, &
Leising, 2009), improvements in student achievement can be realized as a result of teachers
integrating curriculum. Therefore, it is recommended that agriculture teachers collaborate with
their science teacher colleagues in the development and reinforcement of learning resources that
support and supplement the science aspects of the agriculture curriculum.
Moreover, a “communities of practice” should be established between agriculture teachers and
their respective science teacher counterpart. Chalmers and Keown (2006) identified this as a
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April 20-23, 2011
cost-effective practice for providing professional development to teachers, which could also
reinforce the self-efficacy of instructors in teaching the science content inherent to their
curricula. Further, professional development should focus on helping instructors understand the
use and format of the CAERT curriculum better. Specifically, workshops should focus on
helping teachers learn ways to emphasize science concepts effectively as well as assist teachers
in acquiring the pedagogical practices supporting inquiry-based teaching and learning.
Implications
As a result of the curricular intervention, this study showed potential for improving student
achievement in science when curriculum is taught in the context of agriculture. This implication
is consistent with other studies that emphasized science (e.g., Balschweid, 2002; Chiasson &
Burnett, 2001; Ricketts et al., 2006; Roegge & Russell, 1990), as well as different academic
areas such as math (e.g., Parr et al., 2006; 2009; Young, Edwards, & Leising, 2009).
Many of the instructors in this study had 21 or more years of teaching experience (Haynes, 2010)
and all held a science endorsement or certification. Is it possible that having an additional teacher
certification in science, some of the teachers may have actually taught science in Oklahoma
before they became an agriculture teacher? If so, this could have been a confounding variable
that affected the study’s results.
Is it possible that this discovery added to the effects of the science-enhanced curriculum making
it more effective for a contextual learning experience? Dewey (1938) argued for the integration
of academics and vocational training as a way to reinforce the principles of learning thereby
allowing for the development of life skills readily transferable across contextual areas. That
position speaks to the potential for a science-enhanced curriculum being effective, regardless of
students’ prior instructional experiences.
Perhaps an increased amount of time exposing students to the science-enhanced CAERT
curriculum would have had a stronger effect on their science achievement. Parr et al. (2009), in
their study on the selected effects of a curriculum integration intervention on the mathematics
performance of secondary students enrolled in an agricultural power and technology course,
stated that, “perhaps the short time period over which this study was conducted (i.e., one
semester) did not allow sufficient opportunity for significant differences in student math
achievement to emerge. . . ” (p. 66).
Likewise, perhaps the short duration (i.e., the spring 2010 semester) during which this
intervention occurred did not provide enough time for significant differences in students’ science
achievement to emerge. Is it also possible that the comparison group teachers were doing a good
job of emphasizing the science inherent to agriculture in the traditional curriculum already?
Maybe teachers in Oklahoma were teaching a high level of science in their classes already. If so,
this could account for the lack of a statistically significant difference in science achievement
favoring the treatment group. Additional research should address these and related questions.
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April 20-23, 2011
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Diffusion of the Animal Health Network:
Understanding Perceived Characteristics that Can Impact Adoption
Lori L. Moore, Theresa Pesl Murphrey, Shannon H. Degenhart, Tom A. Vestal, Shavahn Loux
Texas A&M University
Abstract
The diffusion of a concept requires careful thought as to how the concept will be perceived by
those involved. The Animal Health Network concept is an innovation that evolved from a 2006
needs assessment which identified the primary source of information for non-commercial
livestock and poultry owners as word of mouth from trusted individuals, feed retail owners, and
local Extension educators. Thus, the Animal Health Network was designed to connect state
veterinarians with Extension partners and local feed retailers to deliver timely, relevant animal
health related information to this audience. The purpose of this study was to explore perceptions
of key opinion leaders related to the characteristics of the Network as an innovation. Qualitative
interviews were conducted with13 stakeholders involved in the implementation of the Network.
The study’s theoretical framework was rooted in Rogers’ Diffusion of Innovations. Close
examination revealed that relative advantage, complexity, and compatibility were readily
apparent to the participants, while trialability and observability were not as pervasive in the
interviews. Key points resulting from the study can assist in the diffusion of the Network
described, and may also benefit others who are working in similar settings or attempting to
diffuse a concept or idea with similar characteristics.
Introduction and Literature Review
The National Institute of Food and Agriculture (NIFA), formerly known as the Cooperative State
Research, Education, and Extension Service (CSREES), is one of four agencies within the
Research, Education, and Economics (REE) division of the United States Department of
Agriculture (USDA). According to the NIFA (2010), “The USDA-REE agencies provide federal
leadership in creating and disseminating knowledge” and “NIFA’s unique mission is to advance
knowledge for agriculture, the environment, human health and well-being, and communities by
supporting research, education, and extension programs in the Land-Grant University System
and other partner organizations” (n. p.). The establishment and diffusion of the innovation under
study has the potential to support that mission through the establishment of a mechanism to
provide time-sensitive, critical, animal health information to underserved audiences.
“Since its inception, the main purpose of the Cooperative Extension Service has been to change
human behavior by teaching people how to apply the results of scientific research” (Rogers,
1963a, p. 16). Rogers goes on to assert that, “The original purpose of the Cooperative Extension
Service, as stated in its Smith-Lever birthright, make it plain that Extension workers are change
agents and that diffusion of new ideas is a central concern” (Rogers, 1963a, p.17). The economic
uncertainty facing the world today has called for many organizations, including local and state
partners of the NIFA, to reexamine the ways in which they do business. “Cultural and
technological changes are quickly outpacing the traditional Extension delivery model.
Extension’s next generation of customers, the techno-savvy generation, will make this even
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truer” (Accenture, 2003, p. 5). Extension partners at many land-grant universities are now faced
with the need to serve increasingly diverse populations with reductions in state support. How
these organizations become 21st century versions of themselves while still remaining true to their
roots is a topic of much debate.
Extension leaders are often referred to as change agents and are responsible for facilitating
changes such as the adoption of new technologies and processes. The study of the diffusion and
adoption of agricultural innovations is not a new field of study. In fact, “…diffusion research
was begun by Extension Service program evaluators” (Rogers, 1963a, p. 17). While studies such
as that of Ryan and Gross (1943) focused on the diffusion and adoption of seed corn in Iowa,
others have examined the diffusion and adoption of information technology (IT) and distance
education (DE) innovations (Hall, Dunkelberger, Ferreira, Prevatt, & Martin, 2003; Harder &
Lindner, 2008; Miner & Harris, 2001; Murphrey & Dooley, 2000).
Miner and Harris (2001) examined factors influencing the adoption of Extension technology
developed to expedite the transfer of ideas or applications, in this instance the PowerPay Debt
Reduction software. Respondents in their study represented Extension, Military, and Business
users. The authors concluded that Extension clientele will readily adopt software that is easy to
use and of high quality.
More recent studies have examined the diffusion of information through various types of
information networks (Harder & Lindner, 2008; Shuffstall, Alter, Bridger, & Sager, 2007;
Swann & Einstein, 2000). Networks can consist of individuals or organizations who share
information, ideas, resources, and/or services to facilitate goal accomplishment (Jackson &
Maddy, n.d.). Swann and Einstein (2000) explored the usage of the Aquaculture Network
Information Center (AquaNIC) Web site launched in 1994. In their study, during the time period
from September 1994 through August 2000, 708 unique visitors accessed approximately 5000
pages of on-line materials per day. Their study focused on an online network but, ultimately,
Swann and Einstein (2000) recommended increased collaboration between Extension and Sea
Grant partners in delivering educational programs that meet the needs of the aquaculture
community.
Shuffstall et al. (2007) explored the concept of third generation community networks “that
engage leaders and organizations in a geographic community in projects that speed up the
diffusion and adoption of information technology across all sectors of the community” (The
Evolution of Community Networks section, para. 5). While their study dealt primarily with
encouraging the adoption of digital tools, Shuffstall et al. (2007) nonetheless concluded that,
“Extension educators can expand their professional networks and affect a wider range of
stakeholder groups through participation in community network projects” (Conclusion section,
para. 3).
Previous studies have documented various aspects related to the adoption of information and
technology related innovations within the field of agriculture. However, there is still room for
improvement. In fact, it is becoming increasingly important for agricultural operations to take
advantage of the advances in information technology (IT) that have occurred within the last 20
years (Thomas & Callahan, 2002). Other facets of the agricultural industry, such as aquaculture
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(Swan & Einstein, 2000), organically grown foods (Middendorf, 2007), and forestry (Bardon,
Hazel, & Miller, 2007) have examined how to best communicate timely information to targeted
populations within their industry.
The Innovation – The Animal Health Network
The Animal Health Network concept is an innovation that evolved from a 2006 needs assessment
conducted in three [state] regions by the National Center for Foreign Animal and Zoonotic
Disease Defense (FAZD Center), a Department of Homeland Security University Center of
Excellence. The needs assessment identified the primary source of information for noncommercial livestock and poultry owners (NLPO) as word of mouth from trusted individuals,
feed retail owners, and local Extension educators. A recommendation of the needs assessment
was the creation of an emergency education and communications network utilizing the existing
Cooperative Extension system in each state and local feed retailers to deliver timely and accurate
animal disease related alerts and information from the state animal health or public health
veterinarian to NLPO. Implementing such a network would contribute to the protection of the
nation’s agricultural infrastructure by reducing the potential negative impact of disease outbreaks
such as the 2003 Exotic Newcastle Disease (END) outbreak in Southern California which existed
in backyard flocks for nearly six months before detection. Within six months of detection over 2
million birds were depopulated, affecting 13 commercial flocks, over 1900 private premises, and
three states (Highfill, 2003). Nine months after detection, the estimated direct trade impact to the
United States was $77 million with an indirect trade impact of $74 million (USDA-APHIS,
2003). Early detection and reporting by NLPO could have significantly reduced the negative
impact of this disease on producers, California’s agricultural infrastructure, and national trade.
The goal of the Animal Health Network is to connect state veterinarians with Extension partners
and local feed retailers to deliver timely, relevant animal health related information to NLPO.
The network has the potential to help Extension partners meet the needs of their ever-changing
clientele while serving hard to reach populations. The Network is intended to operate by
enabling state veterinarians to send alerts to state Extension partners who in turn pass the alert to
feed retailers who post printed alerts in highly visible areas for NLPO to view and use when
making decisions. In December 2009, one state initiated a state-wide adoption of the Animal
Health Network. This study examines the perceived characteristics of the Network as an
innovation that can impact adoption and diffusion. The second research priority area in
Agricultural Communications in The National Research Agenda for Agricultural Education and
Communications (2007) calls for research that answers the questions “How do we reach, create
awareness, and constructively engage the public in high priority agricultural issues?” and “How
do we identify, assimilate, disseminate, format and evaluate relevant information that facilitates
public decision-making about high priority agricultural issues?” (p. 6). This study sought to
address those questions.
Rogers defined diffusion as “the process by which an innovation is communicated through
certain channels over time among the members of a social system” (Rogers, 1995, p. 5). His
classic diffusion model included four main elements: the innovation, communication channels,
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time, and the social system (Rogers, 1995). He also identified four areas of diffusion with
implications for Extension workers: (1) the adoption process, (2) the rate of adoption of
innovations as a function of their characteristics, (3) adopter categories, and (4) opinion leaders
(Rogers, 1963b).
The theoretical framework for this study was rooted in Rogers’ Diffusion of Innovations,
specifically within the first of the four main elements within the theory, the innovation.
According to Rogers (1995) there are five perceived characteristics of innovations that help
explain the rate at which innovations are adopted: relative advantage, compatibility, complexity,
trialability, observability. “Past research indicates that these five qualities are the most important
characteristics of innovations in explaining the rate of adoption” (Rogers, 1995, p. 16).
The first characteristic of innovations is relative advantage. Rogers (1995) defined relative
advantage as “the degree to which an innovation is perceived as better than the idea it
supersedes” (p. 15). Innovations are adopted faster if users perceive them to be better than what
they currently have. The second characteristic of innovations is compatibility which is “the
degree to which an innovation is perceived as being consistent with the existing values, past
experiences, and needs of potential adopters” (Rogers, 1995, p. 15). Innovations that are
consistent with social system values and norms will be adopted at faster rates than innovations
that are incompatible with existing values and norms. In other words, innovations that are similar
to what individuals are already using are more readily adopted. The third characteristic of
innovation is complexity. “Complexity is the degree to which an innovation is perceived as
difficult to use and understand” (Rogers, 1995, p. 16). Innovations that are more complicated and
difficult to learn will be adopted more slowly than less complicated and easier to learn
innovations. Rogers (1995) defined the fourth characteristic of trialability as “the degree to
which an innovation may be experimented with on a limited basis” (p. 16). Innovations that can
be tried before full adoption are adopted at faster rates than innovations that require full
commitment. The final characteristic of innovations is observability. “Observability is the degree
to which the results of an innovation are visible to others” (Rogers, 1995, p. 16). Individuals
adopt innovations in which they can easily see the results from use at faster rates than
innovations in which the results are not readily seen. In summary, Rogers (1995) stated,
“Innovations that are perceived by individuals as having greater relative advantage,
compatibility, trialability, observability, and less complexity will be adopted more rapidly than
other innovations” (p. 16).
As Harder (2009) stated,
It is possible to enhance our opportunities for success in Extension by focusing on factors
related to diffusion. Studying the characteristics of an innovation may help us determine
what to highlight in our marketing, such as when an innovation is less expensive,
increases profit, or is compatible with community values. (p. 3)
Rogers (1995) defined opinion leadership as “the degree to which an individual is able to
influence other individuals’ attitudes or overt behavior informally in a desired way with relative
frequency” (p. 27). It is important to recognize the role opinion leaders play in describing the
characteristics of an innovation. According to Barker (2004), “Diffusion of Innovations theory
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shows that known and trusted opinion leaders in a group or community have tremendous
influence with respect to the acceptance or rejection of innovations” (p. 131). In the end, if key
individuals charged with leading the adoption of the Animal Health Network are aware of the
characteristics of the Network as an innovation, they can increase the speed with which it is
adopted. Perhaps Harder (2009) said it best, “by applying the principles of diffusion to program
development, Cooperative Extension can increase its effectiveness as a change organization” (p.
3).
Purpose
The purpose of this study, conducted as part of a larger study, was to explore perceptions of key
opinion leaders, including Department of Agriculture personnel, Extension administration
personnel, and County Extension Agents, related to the characteristics of the Animal Health
Network as an innovation that was implemented in [state] in December 2009. More specifically,
this study examined opinion leader perceptions related to the relative advantage, compatibility,
complexity, trialability, and observability of the Animal Health Network.
Methodology
Qualitative interviews (Cresswell, 1998; McCracken, 1998) were conducted with a purposive,
voluntary, convenience sample. In order to avoid bias, interviews were conducted by members of
the research team who were external to the organization diffusing the innovation. Thirteen
stakeholders involved in the implementation of the Animal Health Network were included in the
study. The 13 participants consisted of three [state] Department of Agriculture personnel, three
Extension Administration personnel, and seven County Extension Agents. Lincoln and Guba
(1985) defined interviews as “…a conversation with a purpose” (p. 268). Prior to the interviews,
participants were provided the overall goals of the interviews and an interview protocol that
included a potential list of questions. Personal interviews were conducted face-to-face when
possible and were used with six participants. Due to travel constraints, telephone interviews were
conducted with the remaining seven participants. All interviews were conducted over a two day
period and each interview lasted between 30 minutes and one hour. Two of the researchers were
present at each interview. Detailed notes were taken during each interview in an effort to record
all concepts covered by each participant. Following the conclusion of all interviews, interview
notes were reviewed for accuracy. Member checking was accomplished by requesting that
participants review the interview notes and respond with any changes or additions. Triangulation
was addressed by having two researchers present at each interview and providing interview notes
for each participant to review and confirm. A peer debriefing was held with the entire research
team prior to data analysis to “refine and …redirect the inquiry process” (Erlanson, Harris,
Skipper, & Allen, 1993, p. 31) and again following data analysis.
After all interviews had been conducted and transcripts were verified, names were removed from
the data and replaced with a code representing his/her role in the diffusion process. Coding was
implemented as follows: Department of Agriculture (DA); Extension Administration (ExA); and
County Extension Agents (CEA). A number was randomly assigned along with the code.
Confidentiality coding was addressed by randomly assigning numbers as codes. The order of the
interview was not used in the coding to assure anonymity of the participants.
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Data from the 13 interview transcripts were analyzed using deductive content analysis. “Content
analysis is a technique that enables researchers to study human behavior in an indirect way,
through an analysis of their communications” (Fraenkel & Wallen, 2009, p. 472). The transcripts
were analyzed according to an existing framework (Patton, 2002); in this case, Rogers’ (1995)
characteristics of innovations. The transcripts of the interviews were analyzed by two of the
researchers according to the five characteristics of innovations. According to Fraenkel and
Wallen (2009), the determination of themes based on previous knowledge, theory, and/or
experience, prior to data analysis is an acceptable procedure used in content analysis studies.
Data from the transcripts were unitized such that only one of the five key themes was found
within each unit of data (Erlandson et al., 1993). Once data were unitized, the researchers coded
both the manifest content and the latent content of each unit of data (Fraenkel & Wallen, 2009).
Two members of the research team coded the responses collectively to ensure consistency of
coding. Codes and themes were utilized to organize the content and arrive at a narrative
description of the findings (Fraenkel & Wallen, 2009). Trustworthiness was established in this
study through prolonged engagement (the researchers were in contact with those to be
interviewed two months prior to actual face-to-face meetings), member checks, peer debriefings,
and triangulation.
Results
Content analysis of the interview transcripts revealed participants were able to describe the
Animal Health Network in terms of its relative advantage, compatibility, complexity, trialability,
and observabilty. While all five characteristics were identified within participant interviews, the
trialability and observability characteristics were not as pervasive in the interviews as the other
characteristics. It is important to note that while the Animal Health Network has been
implemented in [state], it will not officially be utilized until an emergency situation occurs.
Relative Advantage
Relative advantage, as shared by Rogers (1995), relates to an idea being better than the current
idea in place. As noted by all of the participants, there is a need for a mechanism to distribute
critical animal health information to backyard livestock and poultry owners. Small scale farms
do not go through formal licensing procedures (DA01), are not accessible through the same
venues as commercial groups (DA01, DA02), and have the potential to be missed or overlooked
during a crisis (CEA04). Thus, the relative advantage of the Animal Health Network was
communicated as being strong. Respondents indicated that the Network had value (CEA01),
provides a linkage between communities and Extension (CEA02, CEA05, CEA07), and
encourages partnerships between retailers and Extension (CEA03). It was also communicated
that the Network allows one to “do more with less” (CEA06) – indicating that the Network can
allow a broader reach to the intended target audience of non-commercial producers. Additional
elements related to relative advantage included the important role that Extension plays in the
diffusion. It was shared that regulatory agencies such as Departments of Agriculture were not
the appropriate venue for sharing of information due to concerns of trust with clientele (DA01);
thus, a strong element of the Network is the involvement of Extension in the process. Relative
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advantage is further enhanced through current involvement in the community by Extension
(DA03).
Complexity
Rogers described “complexity” as the degree to which something is easy or hard to use and
understand. Respondents overwhelmingly indicated that the Network concept itself needs to be
“easy” to understand (CEA01, CEA05, CEA06). In fact, it was shared that the simplicity of the
Network concept could actually confuse participants (ExA02). While the concept of sharing
information is a straight forward process – it is critical that those receiving the information
recognize that the information is coming from a recognized and reliable source (CEA04). Issues
related to complexity included: importance of keeping the Network on the radar of participants
(CEA03); providing a clear understanding of the goal of the Network (CEA03); keeping
regulation separate from alerts (CEA04); locating accurate contact information for feed retailers
(CEA06); dealing with issues related to large chain retail stores (CEA07, DA01); and appropriate
use of technology to make contacts (ExA02). The characteristic of “Complexity” is one that
changes depending on the individual and their perceptions. The Network is a simple, straightforward concept; however, the importance of clear communication and accountability was
communicated as being critical by respondents.
Compatibility
Rogers defines compatibility as the degree to which an innovation matches with one’s values,
needs, and prior experiences. As such, the Network was communicated by respondents to have
aspects that were in some ways compatible and in other ways in conflict. One respondent
indicated that feed retailers might not be comfortable being a part of the Network (CEA01).
“People in agriculture in general may be more resistant to being on a list, statewide or
nationwide. They think if they say something, someone is going to show up at their farm as a
regulator” (CEA01). As such – it was shared that the Network should be used for only
emergencies and not as a way to communicate non-emergency information (CEA03). Another
aspect of compatibility related to chain stores (i. e., Tractor Supply). While it should be noted
that chain stores are not intended to be a key component of the Network, several respondents
indicated that feeds are purchased from these locations and that these stores should be
considered. Given that these stores must report to corporate entities – it is harder for them to
easily agree to distribute information (CEA03). Thus, the Network is not readily compatible
with this type of situation without additional levels of approval.
The importance of “trust” (CEA04, CEA06) was articulated as a critical element of
compatibility. As shared by one respondent, feed retailers should not be harassed for being a
part of the Network (ExA02). Access to technology such as email and fax was also indicated as a
potential barrier that could impact compatibility (DA02, CEA07). Based on respondent
comments, face-to-face delivery of messages may be required in emergency situations in some
cases. Overall, respondents indicated that the Network was compatible with getting the message
to the intended audience (DA01); however, respondents noted that it is important to demonstrate
the importance of the Network (DA02, ExA02).
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April 20-23, 2011
Trialability
Rogers defines trialablity as the degree to which an innovation can be tried out on a small scale.
While it is possible to send test messages through the Network, it was noted by respondents that
until an emergency happens, it is difficult to see the Network as what it is – a means of providing
emergency information to non-commercial livestock and poultry owners (ExA02). One
recommendation was to use 4-H and livestock clubs as locations for beta testing the Network
(CEA01). Only limited comments were provided by respondents regarding trialability.
Observability
Observability relates to being able to see the results of adopting a particular innovation. In the
case of the Network, results become more observable once the Network is used for crisis events.
Until that time, the observability of the innovation can be quite low. As shared by one
respondent, “People may have a harder time understanding the value of the Animal Health
Network if they haven’t had the disease challenges that we have” (DA03). Many of the
respondents indicated the need for the Network to be used periodically in order to keep those
involved aware (CEA01, CEA03). Additional elements related to observability included
providing examples of how the Network can increase safety (CEA02), promoting the Network as
a service to benefit animal agriculture (CEA02), and providing a visual map of participation
(CEA06). Observability will be most apparent in the “middle of an emergency” (ExA02), until
that time, observabliity may be limited because the benefit will not be seen until there is an
outbreak (ExA01).
Conclusions and Discussion
In considering the Animal Health Network as an innovation and the diffusion of that innovation,
it is important to recognize that buy-in is needed in order to facilitate adoption. Thus, an
understanding of the characteristics of the innovation itself can help one develop strategies to
improve the chance of adoption and long-term retention and use. By analyzing the transcripts of
interviews conducted with 13 individuals involved in the implementation of the Animal Health
Network, the researchers were able to conclude that three of the five characteristics of
innovations outlined by Rogers (1995) were apparent to the participants.
The Animal Health Network was perceived to have relative advantage and offer a solution to
reach non-commercial livestock and poultry producers, who are a hard-to-reach population. In
addition, it can be concluded that implementation of the Network could strengthen ties between
Extension and rural communities. However, it also became apparent that while the concept of
the Network is a very straight-forward concept, there are aspects that create complexity. Given
that the Network is a venue that is only to be used for emergencies; concern was shared
regarding maintenance and recognition of the Network. Based on findings, one can conclude that
effective adoption will require efforts to provide Network visibility. Another aspect of
complexity relates to the importance of keeping “regulation” and “regulation entities” separate
from the Network. Based on responses, it can be concluded that involvement of any regulation
entities in the implementation of the Network increases complexity and could create a negative
response by participants and negatively impact adoption. Further, it is important to recognize that
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while feed retail chains were not intended to be included in the Network, the role that these
entities play in providing feeds to non-commercial livestock and poultry producers cannot be
overlooked. Efforts must be made by Network administrators to inform and involve chain stores
to ensure that all appropriate venues are used in distributing emergency information, while at the
same time mitigating issues that can arise through lower-level contact with these entities. This in
turn could increase compatibility by addressing the concerns regarding the high use of chain
stores and the need to reach clientele through these venues. The issue of “regulation” was also
found to be associated with compatibility. The concept of being “put on a list” is not readily
compatible with individuals in rural communities. Thus, “trust” is a critical element of Network
implementation. Access to technology such as fax or email was also found to be an element that
could impact compatibility. Efforts must be made to overcome lack of technological access.
It was concluded that the Animal Health Network was not perceived by respondents to have a
high degree of trilability or observability. As noted by respondents, due to the nature of the
Network - it is only observable during an emergency and it is not easily experimented with. It
will be important during the diffusion of the Network to provide visibility to the Network
through promotion efforts that focus on benefits that relate to safety, health, and economics.
Implications for Practice and Future Research
Had the researchers analyzed the responses from an inductive lens, several issues related to the
process of adopting the Animal Health Network would have emerged in addition to the five
characteristics of innovations discussed in this paper: the importance of relationships within the
adoption process, working with feed retailers when management is not present, working with
large chain retailers with corporate offices, incentives and monetary benefits for feed retailers,
the need to incorporate local veterinarians into the Network, and the need to connect the Network
across states. The researchers suggest further research to better understand the impacts of these
issues on the adoption of the network.
In addition, there are several implications for practice that were revealed in the findings. The
diffusion and adoption of concepts and ideas are quite different than that of an item – the process
requires careful thought as to how the concept or idea will be perceived by those that are
intended to be involved in the implementation or use of the concept or idea. In this case – the
idea is the process of providing emergency information to non-commercial livestock and poultry
producers via Extension employees through feed retailers. Findings reveal that while the
Network is perceived to have relative advantage, be compatible with current practices, and not be
overly complex, observability and trialability are not readily apparent or easily increased.
Making the Network more observable must be done in a way that does not distract from the
overall purpose of solely providing emergency information, and allowing for trialability requires
creative efforts on the part of those diffusing the innovation. The implementation of the Animal
Health Network requires commitment and buy-in from all individuals in the process including
the state veterinarian, Extension administration, Extension employees, and feed retailers.
Recognition of the five characteristics of the Network can assist in the development of diffusion
strategies that can be successful. Key points include: do not include regulatory agencies in the
process, provide visibility to the Network without overuse for non-emergency purposes, build
relationships and trust with those involved, and emphasize the importance of the Network based
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on past experiences. Careful consideration of these points can assist in not only the diffusion of
the Network described but may benefit others that are working in similar settings or attempting
to diffuse a concept or idea that has similar characteristics.
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12
April 20-23, 2011
Essential Agricultural Mechanics Skill Areas for Early-Career Missouri Agricultural
Educators: A Delphi Approach
Billy McKim, Texas A & M University
Abstract
According to the National Research Agenda for Agricultural Education and Communication,
pre-service agriculture teacher education programs should “prepare and provide an abundance
of fully qualified and highly motivated agricultural educators at all levels” (Osborne, n.d., 8).
The lack of preparation of entry career agricultural educators is no more apparent than in the
curriculum area of agricultural mechanics. Furthermore, Saucier and McKim (2010) stated that
all school-based agriculture educators who instruct agricultural mechanics must be technically
competent and be able to safely manage the school laboratory for effective student instruction.
The model for teacher preparation in agricultural education (Whittington, 2005) served as the
conceptual framework. The study sought to determine the essential agricultural mechanics skill
areas that Missouri agriculture educators must possess prior to beginning a career in
agricultural education. Results of this study identified essential agricultural mechanics skill
areas that range from laboratory management to soldering. Teacher educators and state
supervisory staff should review these skill areas and plan professional development education
for current Missouri agricultural educators who have in-service needs in these skill areas.
Additionally, pre-service programs in Missouri should be evaluated to determine if effective
teachers are being prepared in the curriculum area of agricultural mechanics.
Introduction
―
Changes in the economy, work, and society demand that every high school student be
prepared both for careers and post secondary education‖ (Brand, 2003, p. 7). Establishing a
connection between core subject matter and agriculture provides for authentic learning by
establishing real-life applications to general or abstract principles (Parr, Edwards, & Leising,
2008). Agricultural education programs further allow students to develop both academic and
vocational skills through hands-on learning opportunities (Hubert, Ullrich, Lindner, & Murphy,
2003) or meaningful application (Parr et al., 2008).
It is no longer appropriate to dichotomize secondary education into preparation tracks for
college or for work (Brand, 2003). Thus, it is important for educators to find appropriate avenues
to promote the evolution of secondary education from ―…
a narrowed discussion of a rigorous
standard academic model targeted to higher achievement scores and a high school diploma to a
model that encompasses rigor, relevance, and relationships targeted to meaningful postsecondary
education and employment‖ (Guy, Sitlington, Larsen, & Frank, 2009, p. 39). One such proposed
method of accommodating this transition has been the integration of science, technology,
engineering, and mathematics (STEM) into agricultural mechanics curriculum (Parr et al., 2008).
Integration of mathematics or science into agriculture mechanics curriculum has been
reported as a method of connecting core subject matter with meaningful application (Parr et al.,
2008). Unfortunately, integration of current technological advances in agriculture has been
April 20-23, 2011
identified as one of the highest-rated needs of pre-service and in-service agriculture teachers
(Duncan, Ricketts, Peak, & Uesseler, 2006). Integration of STEM into agriculture curriculum is
beneficial and is already well noted in the literature (Kotrlik & Redmann, 2009; Myers, Dyer, &
Washburn, 2005; Thoron & Myers, 2010; Warnick, Thompson, & Gummer, 2004). It is,
however, unlikely that beginning teachers will succeed in integrating STEM into their courses
without adequate preparation at the pre-service level. Therefore, it is important to identify the
needs of beginning agricultural educators, especially the relevant skills that link
classroom/laboratory instruction to real-world application (Hubert et al., 2003; Parr et al.,
2008)— these skills are included in agricultural mechanics curriculum.
Teachers who have completed no more than three years of teaching have been classified
as beginning teachers (Huberman, 1989; Myers et al., 2005). Clearly identifying the in-service
needs of beginning teachers has been difficult, even through the use of various instruments and
designs (Birkenholz & Harbstreit, 1987; Joerger, 2002; Myers et al., 2005), and from various
perspectives (Garton & Chung, 1996). Variation between individual programs has been
purported as a possible cause of difficulty in identifying the in-service needs of beginning
teachers (Birkenholz & Harbstreit; Myers et al., 2005). Nonetheless, the consequence of not
understanding those needs is likely to be negative (Myers et al., 2005), possibly even
contributing to higher rates of teacher attrition.
―
The shortage of qualified agriculture teachers is the greatest challenge facing FFA and
agricultural education‖ (National FFA Organization, 2010, para. 2), and is well noted in the
literature (Camp, Broyles, & Skelton, 2002; Connors, 1998; Myers et al., 2005). Furthermore,
the No Child Left Behind Act mandates highly qualified teachers—without limitation to
classroom instruction—for good reason: More than 11,000 school-based agriculture teachers
deliver ―
innovative, cutting-edge and integrated curriculum to students…‖ of which, 59% offer
agricultural mechanics courses (National FFA Organization, 2010, para. 2). Much of the
instruction of agricultural mechanics information takes place in the laboratory setting (Johnson &
Schumacher, 1989) and relies on teachers proficient in agricultural mechanics skill areas
(Saucier & McKim, 2010).
Literature Review
Agricultural education laboratories allow students to actively engage in scientific inquiry
and application (Osborne & Dyer, 2000). Knowledge and skills associated with agricultural
mechanics education are essential for agricultural educators who intend to provide a safe and
efficient laboratory learning environment for agricultural mechanics students (Saucier,
Schumacher, Funkenbusch, Terry, & Johnson, 2008). Administrators rely on the knowledge and
expertise of agriculture teachers to provide high-quality instruction in a safe environment for
school age students (Dyer & Andreasen, 1999; Gliem & Miller, 1993; McKim, Saucier, &
Reynolds, 2010). Furthermore, parents demand that their children receive safe and proper
instruction with adequate supervision from qualified individuals (Dyer & Andreasen). Therefore,
safety is the single most important consideration when teaching in a laboratory environment
(Dyer & Andreasen) and is the primary responsibility of the teacher (Gliem & Miller).
Agricultural mechanics courses continue to be one of the most popular course options for
Missouri agricultural education students (T. Heiman, personal communication, September 2,
April 20-23, 2011
2008). In fact, students list agricultural mechanics and technology as their most popular future
career choice (Missouri Department of Elementary and Secondary Education, 2010).
In a 2008 study by Saucier, Schumacher, Funkenbusch, Terry, and Johnson, it was found
that Missouri agriculture teachers had an average of 11 college credit hours of agricultural
mechanics education. In a similar study of the same population conducted in 1990, Missouri
teachers had an average of over 17 college credit hours in agricultural mechanics education
(Johnson, Schumacher, & Stewart, 1990). Currently, agricultural teacher education degree
programs from the various institutions within the state of Missouri, on average, only require
graduates to possess slightly over eight credit hours of agricultural mechanics education (College
of the Ozarks, 2010; Missouri State University, 2010; Northwest Missouri State University,
2010; University of Missouri, 2010; University of Central Missouri, 2010). Although this
statistic may seem isolated to the state of Missouri, past national studies have found even less
stringent standards. In a national study of 59 universities that educate new agriculture teachers,
Hubert and Leising (2000) found that the majority of pre-service programs required less than
three hours of agricultural mechanics coursework for teacher certification.
Researchers in several states have reported that school-based agriculture teachers had
professional development needs in the area of agricultural mechanics: Kansas (Washburn, King,
Garton, & Harbstreit, 2001), Louisiana (Fletcher & Miller, 1995), Missouri (Johnson &
Schumacher, 1989; Johnson, Schumacher, & Stewart, 1990; Saucier, Terry, & Schumacher,
2009), Nebraska (Schlautman & Silletto, 1992), Texas (Saucier, McKim, Murphy, & Terry,
2010) and Wyoming (McKim, Saucier, & Reynolds, 2010). Researchers have also concluded
that recent graduates of agricultural teacher preparation programs were deficient in aspects
related to agricultural mechanics instruction (Barrick & Powell, 1986; Birkenholz & Harbstreit;
Dyer & Andreasen, 1999; Swan, 1992). Following a review of the literature, it can be posited
that agriculture teachers, at all career levels, have professional development education needs in
the area of agricultural mechanics.
Recently, McKim, Saucier, and Reynolds (2010) noted laboratory safety, laboratory and
equipment maintenance, and laboratory teaching as the areas of greatest need for Wyoming inservice teachers in their study—ranging from one to 35 years of experience. Using the same data
collection instrument, Saucier and McKim (2010) conducted a study of student teachers in
Texas. They also noted laboratory and equipment maintenance, laboratory safety, and laboratory
teaching as the areas of greatest need for the student teachers in their study. Although the studies
used the same data collection instrument, a comparison cannot be made to assert whether
agricultural mechanics laboratory management competencies of beginning teachers are different
than those of tenured teachers. Furthermore, Burris, McLaughlin, McCulloch, Brashears, and
Fraze (2010) compared self-efficacies of first- and fifth-year agriculture teachers in Texas and
reported that efficacy beliefs were stable across career stages of those teachers, which further
raises the question of what agricultural mechanics skills should beginning agricultural educators
possess?
Dewey (1938) is credited for developing experiential learning, which is noted as one of
the ―
philosophical foundations of agricultural education teacher preparation‖ (Whittington, 2005,
p. 92). Without proper pre-service preparation in agricultural mechanics, it is unlikely that
April 20-23, 2011
beginning teachers will be able to effectively use the agricultural mechanics laboratory as a mode
of experiential learning and a tool to provide rigorous and relevant instruction to prepare students
for meaningful postsecondary education and employment. Moreover, effectively using the
agricultural mechanics laboratory to apply and reinforce theory, rather than dichotomously
dividing curriculum instruction into classroom instruction and laboratory activities, (i.e. simply
sending students to the laboratory to work unsupervised) is essential to providing high quality
agricultural mechanics education.
The model for teacher preparation in agricultural education (Whittington, 2005) served as
the conceptual framework for this study. The model (see Figure 1) is based on the philosophical
foundations of agricultural teacher education, experiential learning (Dewey, 1938), problembased teaching (Lancelot, 1944), social cognition (Bandura, 1986), and reflective practice
(Schön, 1983). Coursework aligned with the National Council for Accreditation of Teacher
Education (NCATE) standards, Interstate New Teachers Assessment and Support Consortium
(INTASC) principles, Praxis criteria for licensure, and the American Association for Agricultural
Education (AAAE) standards, guides pre-service teachers to the goal, which includes the
necessary knowledge, skills, and disposition for entry into the teaching profession.
Because many pre-service programs require only three hours of agricultural mechanics
coursework for teacher certification (Hubert & Leising, 2000), it is important to establish the
most appropriate and necessary agricultural mechanics knowledge and skills needed by
beginning teachers. Thus, it is important to accurately identify the essential agricultural
mechanics skill areas needed by beginning agriculture educators.
Figure 1. The model for teacher preparation in agricultural education (Whittington, 2005, p. 94).
Purpose and Research Objective
It stands to reason that if the supply of highly qualified, agriculture teachers is
diminishing (FFA, 2010), then it is also likely that the supply of highly qualified agriculture
teachers with adequate agricultural mechanics education is diminishing as well. Furthermore, the
continuous need for evaluations of teacher education programs (Osborne, n.d.), and the
April 20-23, 2011
continued popularity of agricultural mechanics courses in secondary agricultural education
programs (T. Heiman, personal communication, September 2, 2008), warranted a need to
determine the essential agricultural mechanics skill areas that a new agricultural educator in
Missouri should possess upon the completion of a pre-service agricultural education program.
Therefore, the purpose and objective of this Delphi study was to determine the essential
agricultural mechanics skill areas that beginning Missouri agricultural educators should possess
prior to teaching school-based agricultural education, as reported by a panel of experts.
Methods
For this descriptive study, the Delphi technique was used to determine the essential
agricultural mechanics skill areas needed by beginning Missouri school-based agricultural
educators. The Delphi technique is a ―
group process technique for eliciting, collating, and
generally directing informed judgment towards a consensus on a particular topic‖ (Delp, Thesen,
Motiwalla & Seshadri (1977, p. 168). The Delphi technique is a widely accepted method for
achieving convergence of opinion concerning real-world knowledge solicited from experts in
various areas (Hsu & Sandford, 2007; Ramsey & Edwards, 2010.) Stitt-Gohdes and Crews
(2004) noted that the purpose of the Delphi technique is used to gather responses from an expert
panel or panels, and combine the responses into one useful statement. Furthermore, in
agricultural education, Martin and Frick (1998) noted that the Delphi technique was practical in
planning curriculum and the development of personal qualities of student leaders.
An advantage of this technique is that it helps minimize the typical disadvantages of a
traditional round table discussion. These disadvantages include: bandwagon effect of a majority
opinion, the power of persuasiveness of an individual, the vulnerability of group dynamics to
manipulation, and the unwillingness of individuals to abandon publicly stated opinions (Issac &
Michael, 1987).
The data collection process for a Delphi study consists of a series of four questionnaires
(Isaac & Michael, 1987). The Delphi technique begins with the identification of group members
whose consensus opinions are sought. These group members are commonly known as a panel of
experts. They are identified due to their expert knowledge in the subject matter being studied.
For this study, purposeful sampling was used to select members for the panel of experts.
According to Creswell (2005), purposeful sampling can be defined as ―
a qualitative sampling
procedure in which researchers intentionally select individuals and sites to learn or understand
the central phenomenon‖ (p. 359).
Panel of Experts
The panel of 24 experts for this study were Missouri school-based agricultural educators
with expertise in agricultural mechanics instruction and curriculum. These teachers were
identified by agricultural education district supervisors and the professional development
specialist from the Missouri Department of Elementary and Secondary Education. Contact
information was attained from the 2008-2009 Missouri Agricultural Education Directory
(Missouri Department of Elementary and Secondary Education, 2008). All panelists were
familiar with the entry level agricultural mechanics related technical skill areas needed by new
teachers.
April 20-23, 2011
Instrumentation
Validity (face & content) of the initial instrument used in this study was determined by
two agricultural education faculty members, one agricultural education graduate student with
previous school-based agricultural education instructional experience, a professional
development education coordinator for the state of Missouri, one agricultural education faculty
member with specialization in research methods and instrument design, and one agricultural
systems management faculty member with prior school-based agricultural education
instructional experience. According to Dalkey (1969), one of the original researchers of the
Delphi technique, determined for a Delphi instrument to be reliable (.7 or greater), an panel of
experts must consist of 11 members or more. Furthermore, Dalkey, Rourke, Lewis, and Snyder
(1972) later found that a panel size of 13 was needed in order for an instrument to be reliable
with a correlation coefficient of .9. To ensure the reliability of this instrument, twenty-four
experts were selected to serve on the panel for this study.
Procedures
In the first round of the Delphi technique, the group members generate a list of goals,
concerns, or issues toward which group consensus opinions are desired. The first questionnaire
contained an open ended question that asked the respondents to list all agricultural mechanics
skills that an entry-level Missouri agriculture teacher would need to know prior to starting a
career in secondary agricultural education. The results from round one were collected and
checked for content validity by a panel of experts which included a teacher educator, three
agricultural education graduate students with prior school-based agricultural education teaching
experience, an agricultural systems management professor, and a professional development
specialist for the Missouri Department of Elementary and Secondary Education. The resulting
list of agricultural mechanics skills was reviewed by the researchers and placed into 23 skill
areas that represented common agricultural mechanics skills (see Table 2.) These skill areas were
then used to develop the second questionnaire.
For round two, the members of the group ranked each of the 23 skill areas, that resulted
from round one, from 1 (most important skill) to 23 (least important skill) on questionnaire two.
Respondents were instructed that no skill area may share the same ranking and that each skill
area must be ranked. The responses were then combined to provide a mean group ranking for
each skill area. The researchers then compiled the results of round two and created a new
instrument for use in round 3 (see Table 3.)
For round three, a new questionnaire that contained the same 23 skill areas, listed the
mean group ranking for each skill area, and the individual respondents ranking for each skill area
was developed. The respondents were again asked to rank each skill area now knowing the mean
group ranking and their previous ranking for each skill area. They were also asked to provide
comments if their ranking of a particular skill area differed greatly from the mean group ranking
for each skill area (see Table 4.)
Concluding the results of questionnaire three, the researchers developed a new
questionnaire for round four. The fourth questionnaire included all 23 skill areas, the mean group
rankings for each skill area, the most recent individual respondents ranking for each skill area,
and any comments that the respondents supplied concerning their dissent from group ranking for
April 20-23, 2011
each skill area. The respondents ranked each skill area for the last time knowing the mean group
ranking and their previous ranking for each skill area. The final contact with the group members
was a summary of their ranking of the 23 agricultural mechanics skill areas that a beginning
Missouri agricultural educator should possess prior to teaching school-based agricultural
education (see Table 5.)
Data Analysis
Data relative to research objective one were analyzed utilizing Microsoft Excel®. For
research objective one, the researchers determined the mean ranking, standard deviation, and
rank for each agricultural mechanics skill area.
Results
Round One
As displayed in Table 1, over 75% of the respondents completed all four rounds of the
Delphi study. The response rate for the round one questionnaire was 95.83% (n = 23). The 23
respondents identified 180 essential agricultural mechanics skills that a beginning Missouri
agricultural educator should be proficient in prior to teaching school-based agricultural
education. Similar or duplicated statements (i.e. skills) were combined or eliminated while
compound statements were separated (Shinn, Wingenbach, Briers, Lindner, & Baker, 2009).
These skills were analyzed by the researcher, grouped into 23 skill areas, and were used to
develop the Round 2 questionnaire (see Table 2).
Table 1
Response Rate of Each Delphi Round
Delphi Round
Round 1
Round 2
Round 3
Round 4
%
95.83
83.33
79.16
75.00
Table 2
Essential Agricultural Mechanics Skill Areas Identified in Round One
Skill Area(s)
Building material management
Carpentry
Cold metal work
Concrete
Electricity
Gas Metal Arc Welding (GMAW)
Gas Tungsten Arc Welding (GTAW)
Hand tools
Handheld power tools
Laboratory management
Laboratory safety
April 20-23, 2011
n
23
20
19
18
Measurement tools
Methods used to teach agricultural mechanics
Oxygen/ Acetylene Cutting (OAC)
Oxygen/ Acetylene Welding (OAW)
Plasma Arc Cutting (PAC)
Skill Area(s)
Plumbing
Project management
Shielded Metal Arc Welding (SMAW)
Small gas engines
Soldering
Stationary power tools
Surveying
(Continued)
Round Two
In round two, respondents ranked the 23 agricultural mechanics skill areas, from 1 (most
important skill) to 23 (least important skill), as they pertain to the skills needed by beginning
Missouri agriculture teachers. These skill areas were then used to develop the questionnaire for
round three of the study. The response rate for round two of the study was 83.33% (n = 20).
Panel members identified laboratory safety as the top needed agricultural mechanics skill area
(M = 2.25; SD = 1.62) for beginning Missouri agriculture teachers. Furthermore, panel members
also identified the skill area of soldering (M = 21.60; SD = 2.14) as the least essential agricultural
mechanics skill area for teachers. The remaining results of round two are displayed in Table 3.
Table 3
Ranking of Essential Agricultural Mechanics Skill Areas Identified in Round Two
Skill Area(s)
Mean Rank
SD
Overall Rank
Laboratory safety
2.25
1.62
1
Methods used to teach agricultural
3.50
4.55
2
mechanics
4.60
5.35
3
Shielded Metal Arc Welding (SMAW
7.10
2.36
4
Measurement tools
7.80
4.90
5
7.90
3.31
6
Project management
8.50
5.25
7
8.60
3.41
8
9.10
3.54
9
9.60
3.55
10
9.75
6.02
11
Hand tools
11.15
4.94
12
Carpentry
12.80
3.71
13
Electricity
13.80
3.22
14
13.80
3.83
15
15.95
5.93
16
(Continued)
April 20-23, 2011
Small gas engines
Cold metal work
Skill Area(s)
Plumbing
Concrete
Surveying
Soldering
16.50
16.50
Mean Rank
16.95
16.95
18.80
21.05
21.60
3.62
4.81
SD
3.22
3.27
3.89
1.67
2.14
17
18
Overall Rank
19
20
21
22
23
Round Three
Respondents again ranked the 23 agricultural mechanics skill areas, from 1 (most
important skill) to 23 (least important skill), in round three of the study. The response rate for
round three of the study was 79.16% (n = 19). Panel members again identified laboratory safety
as the top needed agricultural mechanics skill area (M = 1.35; SD = 0.77) for beginning Missouri
agriculture teachers. Additionally, panel members further identified the skill area of soldering (M
= 21.74; SD = 2.08) as the least essential agricultural mechanics skill area for teachers. The
remaining results of round three are displayed in Table 4. The results of this round were used to
develop the questionnaire for round four of the study.
Table 4
Ranking of Essential Agricultural Mechanics Skill Areas Identified in Round Three
Skill Area(s)
Mean Rank
SD
Overall Rank
Laboratory safety
1.35
0.77
1
2.32
1.42
2
mechanics
3.42
1.98
3
Project Management
6.00
2.16
4
Measurement tools
6.05
3.98
5
Shielded Metal Arc Welding (SMAW)
6.53
2.20
6
7.89
2.66
7
8.21
2.86
8
9.05
2.17
9
10.00
3.06
10
10.37
4.71
11
Hand tools
11.89
4.76
12
Carpentry
12.63
2.65
13
Electricity
14.11
2.47
14
14.68
3.73
15
16.58
3.29
16
Cold metalwork
16.68
3.56
17
Small gas engines
17.21
3.17
18
Concrete
17.95
3.06
19
Plumbing
18.05
2.39
20
20.21
2.88
21
Surveying
21.16
1.61
22
Soldering
21.74
2.08
23
April 20-23, 2011
Round Four
In the final round, or round four, respondents ranked the 23 agricultural mechanics skill
areas, from 1 (most important skill) to 23 (least important skill), as they pertain to the skills
needed by beginning Missouri agriculture teachers for the last time. The response rate for round
four of the study was 75.00% (n = 18). Panel members continued to identify laboratory safety as
the top needed agricultural mechanics skill area (M = 1.50; SD = 0.79) for beginning Missouri
agriculture teachers. Furthermore, panel members also identified the skill area of soldering (M =
22.17; SD = 2.15) as the least essential agricultural mechanics skill area for teachers. The
remaining results of round four are displayed in Table 5.
Table 5
Ranking of Essential Agricultural Mechanics Skill Areas Identified in Round Four
Skill Area(s)
Mean Rank
SD
Overall Rank
Laboratory safety
1.50
0.79
1
2.28
1.36
2
mechanics
3.33
2.03
3
Measurement tools
5.06
2.78
4
Project Management
5.39
2.03
5
Shielded Metal Arc Welding
6.83
1.86
6
(SMAW)
7.61
2.33
7
8.33
2.89
8
8.83
2.73
9
10.39
2.79
10
11.22
4.23
11
Carpentry
12.44
2.15
12
Hand tools
12.72
3.63
13
Electricity
13.61
2.30
14
15.06
3.35
15
16.83
2.20
16
Cold metalwork
16.89
3.38
17
Small gas engines
17.00
3.11
18
Concrete
18.00
3.07
19
Plumbing
18.11
2.49
20
20.50
2.57
21
Surveying
21.00
1.46
22
Soldering
22.17
2.15
23
A panel of experts identified 23 essential agricultural mechanics skill areas that beginning
Missouri agriculture teachers should know prior to starting a career as a school-based
agricultural educator. These skill areas ranged from highly technical (Gas Tungsten Arc
Welding) to simple (hand tools). Laboratory safety was consistently the highest ranked skill area.
April 20-23, 2011
As result of this study, several implicative questions arise. Are preservice institutions in
Missouri preparing new agriculture teachers with the needed agricultural mechanics skill areas to
be successful upon graduation? If the answer to this question is no, then why are teacher
educators not adequately preparing these new teachers? Furthermore, what professional
development workshops are being provided to existing teachers in the area of agricultural
mechanics skill acquisition? Future research will be necessary to answer these fore mentioned
questions and others.
Based upon the results of this study, the researchers recommend the following actions:
•
Institutions from the state of Missouri should use this list of skill areas and determine if
preservice students are being adequately educated in agricultural mechanics.
•
Teacher educators and state professional development staff should conduct research to
determine the professional development needs of existing agriculture teachers in the area
of agricultural mechanics skill proficiency.
•
Teacher educators and state professional development staff should provide professional
development educational opportunities for teachers based upon empirical research.
•
Researchers should assess the agricultural mechanics technology currently located within
preservice agricultural education programs and compare to the existing technology to the
curriculum taught at the secondary level for relevance.
A shortage of qualified agriculture teachers is an unfortunate reality facing FFA and
agricultural education (National FFA Organization, 2010). The mandate requiring highly
qualified teachers, indicated in the No Child Left Behind Act, further complicates the issue when
considering what constitutes highly qualified—especially in the laboratory setting. Therefore,
teachers who are responsible for providing laboratory instruction and management must be
highly qualified in areas beyond classroom instruction.
It is imperative that teacher educators, cooperating teachers, student teachers, and
university administrators develop and follow an agreed upon plan of field-based experiences to
provide student teachers an opportunity to develop or expand skills and knowledge that may not
be adequately provided for in their respective teacher education programs (Findlay, 1992).
Although the focus of this study was beginning teachers, it should also be noted that the voids in
teacher preparation programs are not new (Dyer & Andreasen, 1999); thus, further research is
necessary to determine agricultural mechanics skill area needs of in-service teachers.
April 20-23, 2011
References
Barrick, K. R. & Powell, R. P. (1986). Assessing needs and planning inservice education for
first-year vocational agriculture teachers. Paper presented at the 13th Annual National
Agricultural Education Research Meeting. Dallas, TX.
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April 20-23, 2011
Ethnography Study to Evaluate the Effects of Community Markets for
Conservation in the Central Luangwa Valley in the Mfuwe District of Zambia
Caleb D. Dodd, Wyatt DeJong, Brad Leger, Ph.D., Scott Burris, Ph.D.
Community Markets for Conservation (COMACO) is a novel, emerging non-profit
company in Zambia that is pioneering an innovative way for making markets and conservation
work together. With a deteriorating economy, Zambians are in need of sustainable agriculture
that promotes food security and wildlife conservation through education and empowerment. The
purpose of this study was to evaluate the effects that COMACO is having on the social,
economic, and environmental conditions of residents in the Luangwa Valley. A qualitative
ethnography approach was employed as the methodology. The research conducted by students
from the Midwest and Southwest United States includes personal interviews, observations, and
experiences from a three week service-learning project in the Mfuwe district sponsored by a
youth leadership organization’s foundation with funding from the a private foundation.
Researchers documented their experiences in journals and field notes. The founder and CEO of
COMACO, along with employees, local residents, COMACO producers, and non-COMACO
producers were interviewed to provide researchers with an overview of the COMACO model.
The results indicate COMACO is promoting food security using sustainable agricultural
production methods. Food security leads to an increase in household income which leads to
higher education for local children. The COMACO model is a valuable tool for distributing
information from management to individual producers as well as collecting performance records
on specific crops and practices. The need for financial training and record keeping became
evident as a result of this study. COMACO’s local organizational structure enhances livelihoods
and skills while encouraging ownership.
Introduction
Zambia was once classified as a middle-income country, but after three decades of
economic decline and deteriorating infrastructure and services, the country has became
increasingly impoverished. Presently three out of four Zambians live in poverty and more than
half are extremely poor, unable to meet their minimum nutritional needs (Rural Poverty Portal,
2010). Food security measures a family’s ability to cope with hunger is a constant preoccupation
for Zambian families (Lewis & Jackson, 2005). Geographical factors are at the roots of severe
rural poverty in large parts of Zambia. The country suffers from geographical isolation, which
limits access to services, markets, technical knowledge, and productive assets (Rural Poverty
Portal, 2010).
Community Markets for Conservation (COMACO) promotes training in conservation
farming, crop rotation, the use of organic fertilization, and crop diversification as well as
develops markets that drive the adoption of these skills (Poor Market Development, 2010). The
program teaches farmers in the Luangwa Valley to produce enough food to feed their families
and earn income from crop surpluses which support child education and other basic needs
(Hunger and Poverty, 2010).
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COMACO is a non-profit company that receives supplemental funding from a number of
organizations outside of Zambia. Dale Lewis, founder of COMACO, began his career in
conservation due to his desire to study the native elephants of Zambia (D. Lewis, personal
communication, August 2, 2010). Many Zambians resort to poaching to provide their families
with a source of income and food security even though the Zambian Wildlife Authority (ZAWA)
enforces harsh punishments for poaching (D. Lewis, personal communication, August 3, 2010).
Lewis envisioned a program that would educate Zambians in sustainable agricultural production
practices and provide markets for farm produce to develop infrastructure and generate income in
the region. Lewis’ goal was to establish a market for goods produced using conservation
techniques to protect wildlife and secure food for Zambians.
Since the establishment of COMACO in 2003, Lewis sought to create a self-sustaining
company. Now in its seventh year, COMACO still depends on funding from private sources, but
it continues to expand across Zambia (D. Lewis, personal communication, August 2, 2010). In
August of 2010, COMACO had more than 35,000 producers in seven different regions in central
eastern Zambia. COMACO also employed over 300 local workers in a variety of positions in
management, extension, processing, transportation, and marketing of the goods (S. Banda,
personal communication, August 5, 2010).
The purpose of this study was to determine the effects that COMACO is having on the
social, economic, and environmental conditions of the Luangwa Valley in the Mfuwe district of
Zambia. This ethnography study sought to explore the effectiveness of COMACO on providing
food security through sustainable farming and conserving wildlife through production
agriculture. It is important to note the researchers had limited access to information about factors
that impact the long-term viability of COMACO and its supplemental funding strategies.
Consequently, the observations contained in this ethnography do not allow judgments to be made
about the sustainability, scalability, or successful replication of the COMACO model. The study
was guided by three objectives:
1. Evaluate the ability of COMACO to establish food security and increase household
income for small-scale producers.
2. Explore the effectiveness of the COMACO model in transferring knowledge from
management to the producers and recording producers’ performance and yields.
3. Discover the producers’ knowledge of record keeping in production finance.
Methods of Research
In order to evaluate a program in its natural setting, qualitative case study research is
common in the field of education (Gall, Borg, & Gall, 1996). In an effort to determine the
effectiveness of COMACO in the Central Luangwa Valley of the Mfuwe district, in Zambia, an
ethnography study was conducted. Ethnography research is a systematic way of gathering data
using qualitative methods, including participant observation, interviewing, the collection of
April 20-23, 2011
analysis of various documents or artifacts, individual narratives with focus on the social
environment including physical spaces, customs and culture (Savin-Baden & Major, 2010).
This study was conducted by a team of two agricultural education students. Researchers
spent 18 days in the valley participating in a service-learning project sponsored through a United
States youth leadership organization with funding from a humanitarian foundation. The
researchers utilized interviews, informal conversations, focus groups and observations to address
the research objectives. The researchers conducted interviews with eight COMACO producers
and 13 non-COMACO producers individually as well as informal interviews with employees of
COMACO in processing goods, management, transportation, and extension to collect
information for the study. The researchers also utilized focus groups and conversations with
local residents to measure COMACO’s effects on the area and the local industry. The focus
groups consisted of both male and female COMACO producers in the Nsefu, Mnkhanya, and
Kakumbi chiefdoms of the Mfuwe district. Non-COMACO producers interviewed were from
the Jumbe chiefdom also in the Mfuwe district. An interpreter was utilized to translate the
questions and answers while interviewing those who were not fluent in English.
Topics discussed during each interview with COMACO producers and COMACO focus
groups included period of time with COMACO; physical improvements since joining
COMACO; families’ nutrition consumption before and after joining COMACO; children’s
education before and after joining COMACO; opinion of conservation farming practices; yields
and crop variety before and after joining COMACO; secondary or supplemental income;
personal record keeping and documentation of production and household finances; personal
ability to save and plan for investments; and the most challenging aspect of conservation
farming. When interviewing non-COMACO members topics discussed included previous
knowledge of COMACO; families’ nutrition consumption; children’s education; previous
experience and opinion of conservation farming; yields and crop variety; secondary or
supplemental income; personal record keeping and documentation of production and household
finances; personal ability to save and plan for investments; and the most challenging aspects of
farming.
In addition to interviewing, researchers observed trainings of producer groups, leadfarmers, and extension staff. Topics covered in the trainings included basin making, compost
building, planting techniques, row spacing, proper data collection procedures for farmer cards,
and the use of the Better Life Book for the transfer of information. The researchers also toured
the fields and villages of both COMACO and non-COMACO producers.
According to Denzin and Lincoln (1994) various methods must be used that develop an
intertwined set of methodological practices allowing for a better perception of the subject matter
at hand. Researchers recorded field notes from interviews and observations in the villages and in
the production fields. Researchers also documented their experiences in daily journals and
reflected regularly on their surroundings and the living conditions of the individuals who were
interviewed. Archived text offer accurate perspectives of participants at a specific time,
eliminating any change of perspective due to post-phenomenon experiences (Gall, Borg, & Gall,
1996).
April 20-23, 2011
The findings were organized in themes coinciding with the guiding objectives. The
thoughts reflected in the findings were based on information obtained from individuals and
collective groups. Researchers analyzed the responses using open and axial coding to identify
dominant themes for each objective. Individual data was collected from 21 producers whose
identities remain anonymous; each interviewee is coded as a number unrelated to his or her name
to provide an audit trail. The individuals were not rewarded for their participation in the
interview, nor were there any incentives for their participation in the study.
The usual measures of validity and reliability generally accepted in quantitative research
are not appropriate for use in phenomenological studies (Patton, 2002). Nevertheless, steps to
minimize errors of interpretation and to control bias remain important. Many qualitative
research methods have controls of reliability and validity built into the study design.
Trustworthiness is to qualitative as validity is to quantitative (Glesne, 2006). Assuring
trustworthiness requires an ethical explanation of research conducted providing enough detail to
demonstrate the researcher’s conclusions make sense (Merriam, 1998). Part of demonstrating
the trustworthiness of data is to realize the limitations of one’s study (Glesne, 2006). The
researchers involved in this ethnography study had no previous training in qualitative research.
According to Glense (2006), trustworthiness is established with credibility, dependability, and
confirmability of the researcher, methods, and findings.
Credibility can be established through triangulation, using multiple data collection
methods, data sources, or perspectives (Glesne, 2006). In this study, triangulation was achieved
through different sources and methods of collecting information from a variety of sources.
Researchers utilized personal interviews, focus groups, observations, and personal experiences
documented during their time in the district. Triangulating the data obtained from the research to
the analyzed texts added credibility to the study.
In qualitative research, external validity cannot be specified, but the researcher can
provide a broad description so someone could transfer the findings to their own situation
(Bloomberg & Volpe, 2008). Because qualitative researchers use small, non-random, purposive
samples, it is statistically difficult to generalize beyond the sample. The sampling techniques
used in qualitative studies do not allow application of findings outside of the participants. The
individuals chosen for this study were chosen based on availability and location. The results of
this research cannot be inferred upon the entire population of COMACO producers, nor can it be
inferred upon the unvisited COMACO regions. It should be noted that the researchers had
limited access to information about factors that impact the long-term viability of COMACO and
its supplemental funding strategies. The observations in this ethnography do not allow
judgments to be made about the sustainability, scalability, or successful replication of the
COMACO model. Findings of the qualitative study can be useful in other situations. The
researcher can achieve transferability by providing a rich explanation of the findings (Bloomberg
& Volpe, 2008). Findings for this study are provided in the next section.
Confirmability can be compared to objectivity in a quantitative study. Findings should be
the result of the research, not the researcher (Bloomberg & Volpe, 2008). Control measures are
necessary to assure accuracy of results presented. Data analysis refers to the categorization and
order of information in such a way as to make sense and to report findings that are factual and
April 20-23, 2011
correct (Brink, 1991). A limitation to an ethnography study is that journal entries, field notes,
and observations are reported directly from the team of researchers without validation. The
documentation for this research is stored in journals and binders in my office.
Findings
The COMACO producers interviewed in the Nsefu, Mnkhanya, and Kakumbi areas have
been with COMACO an average of approximately 4 years. The interviews conducted in the
Jumbe area were with non-COMACO producers. Each of the 13 non-COMACO producers
interviewed had very positive opinions of COMACO; however, these individuals’ understanding
of COMACO was not entirely accurate. The common theme was “COMACO is a company that
focuses on conservation farming and provides a market for producers” (114, female nonCOMACO producer in Jumbe). The non-COMACO producers did not display an understanding
of how COMACO was able to provide a market or the purpose for conservation farming.
Staff and employees of COMACO on a variety of levels appeared competent and
displayed an enthusiasm for the COMACO model, agriculture, and the people of Zambia. The
extension staff viewed COMACO as, “a company that develops individual producers through
food security and the community through conservation practices” (N. Mulambya, personal
communication, August 10, 2010). The leadership of COMACO believed the producer is the
heart of the organization and brings vitality and success to the company. The employees
expressed an appreciation for their occupations and realized that hiring individuals in the
communities boosted the local economy and generated the transfer of money.
Conversations and interviews conducted with third party individuals about COMACO’s
impact in the community included lodge owners, safari guides, secondary school teachers, local
entrepreneurs, and community members. Reflections by these individuals suggested there has
been a positive change in the community economically over the past five years. Perceptions of
COMACO shared by residents reflect there is a high level of integrity and longevity associated
with the company. Based on interactions with these individuals, researchers found that
COMACO is a “household name” with a very positive reputation in the Luangwa Valley.
Findings for Objective 1
Objective one sought to evaluate the ability of COMACO to establish food security and
increase household income for small-scale producers. While touring and interviewing the
producers’ operations, researchers observed a noticeable difference in COMACO villages as
opposed to non-COMACO villages. The improvements to homes and structures that COMACO
producers purchased or were able to build due to an increase in energy from the increase in food
consumption included tin roofs, solar panels, chicken coops, treadle pumps, larger homes, and
larger bins for grain storage. COMACO producers all verified that they had been able to
upgrade their storage units, production equipment, and living facilities over the past three years
whereas only three of the 13 non-COMACO producers interviewed had been able to make any
improvements during the same time. Researchers discovered that nutrition, education, and crop
yields and variety were three major themes that emerged while evaluating the responses to the
interviews.
April 20-23, 2011
Nutrition.
Along with physical improvements, the food consumption and nutrition for nonCOMACO producers was much different than the COMACO members. The food consumption
and nutrition of families before joining COMACO consisted primarily of nshima (maize or rice
based substance that is prepared by mixing the crushed grain meal with water to make a thick
mash). Along with nshima, families consume rape and a few other vegetables and an occasional
protein source. The majority of families reported consuming less than one yard bird each month
prior to COMACO. Producers interviewed reported they felt food insecure at regular times of
the year prior to COMACO. Since joining COMACO, every producer interviewed claimed their
families are food secure and six of the eight individuals can now produce surplus.
Unlike the regions where COMACO had been established, researchers found protein
sources to be limited in the Jumbe area. Eight of the 13 non-COMACO producers interviewed
were not currently food secure. One farmer commented, “The food we produce is the only
source of nutrition we have to rely on” (112, male non-COMACO producer in Jumbe). One
producer reported trading the maize for alternative nutrition sources and other basic needs.
The average family size reported by the COMACO producers was approximately 7
members while the average size of the non-COMACO producers’ family was approximately 8
members. COMACO producers reported consuming more than two birds a month per household
where the average family non-COMACO family consumes less than one bird each month. One
producer commented that “Vegetable and protein consumption has increased in the valley since
COMACO began here” (108, female COMACO producer in Mnkhanya). Based on the data
collected from interviews, the consumption of vegetables, protein, and eggs among COMACO
producers has increased significantly.
Education.
In the Mfuwe district, education for children is a high priority. Government funded
primary schools provide education for children through grade seven. Parents of students
attending grades eight and nine are required to provide supplemental payments for their children.
At these levels, education continues to be primarily funded by the government. Secondary
school is grade 10 through 12, parents are required to make much larger payments for this level
of education, and students are often required to board on the campus. Fees are collected three
times a year, once for each term of three months with a one month break between terms (N.
Mulambya, personal communication, August 17, 2010).
Thirty-one school-age children are represented by the eight individual COMACO
producers interviewed. The COMACO producers indicated, “Before we had access to the
market there was very little hope of sending our children through grade 12” (107, male
COMACO producer in Nsefu). Many COMACO producers felt that with the higher yields and
accessible market, their children now have a much better chance of receiving a complete
education with the possibility of college. Almost half of the producers interviewed claimed to
have money put aside for the purpose of putting their children through school. The attitude
April 20-23, 2011
reflected by non-COMACO producers differed dramatically. For more than 84% of nonCOMACO families, secondary school was not considered an option for their children due to the
absence of monetary income. Of the two non-COMACO producers who could fund their
children’s education, one relied on selling crops to the school to trade for education expenses
(119, female non-COMACO producer in Jumbe) and the other relied on wealthy relatives from
Lusaka, Zambia’s capitol city (120, female non-COMACO producer in Jumbe). On average
about 5 children are represented by each non-COMACO producers, yet not one of these
producers was able to claim that they saved for education expenses of these 59 children.
Crop yields and variety.
In the time that the majority of producers have been with COMACO, producers have
seen their yields increase dramatically. Along with this increase in yields, all eight producers
individually interviewed reported their production of crop variety growing. One COMACO
producer commented:
Prior to COMACO’s involvement in the Mfuwe district, the majority of crops
grown were maize, conventional cotton, rice, cow peas, groundnuts, tomato,
cabbage, and sorghum. With the addition of COMACO to the area, the variety of
crops has grown to also include red and yellow peppers, onions, mustard, spinach,
sweet potatoes, squash, and velvet beans (108, male COMACO producer in
Nsefu).
Along with increased variety, the amount of produce for sale has more than doubled in the area.
According to another producer, “COMACO’s training efforts have made it possible to produce
extra food and to increase the variety of food we can now provide our families” (106, female
COMACO producer in Mnkhanya). Crop variety for non-COMACO farmers was limited and
included cotton, maize, groundnuts, and cow peas. The following crops were also reported to be
grown in the area on a very small scale: bananas, sugar cane, cassava, and tomatoes. The
reported yields were less than half of those collected from the fields of COMACO producers.
The most noteworthy finding was that no outside market existed for the commodities. One nonCOMACO producer commented, “The lack of market causes us to rely only on local consumers
for a small market. We have no reason to produce an excess of goods after we supply our own
consumption” (116, female non-COMACO producer in Jumbe). This lack of motivation is due
to the restraints of not having a market for their goods and few opportunities for selling produce
for income.
All but one of the non-COMACO producers stated that their major challenge was not
having a market for surplus produce. Without markets, producers are forced to sell or trade their
produce at very low cost to prevent produce from going to waste. In order to sell to COMACO,
non-COMACO farmers must meet the same standards of production as the COMACO members
and COMACO must have a shortage of that particular produce. Non-COMACO producers are
not given the premium for their produce as COMACO members.
April 20-23, 2011
The second objective explored the effectiveness of the COMACO model in transferring
knowledge from COMACO’s management to the producers and recording producer’s
performance and yields. COMACO’s organization strategy for getting information to the
producer was developed to emphasize the importance of each producer. Producers are organized
into groups of a maximum of 15 individuals; each group elects a chairperson from within the
group (S. Bunda, personal communication, August 3, 2010). For every three groups, one group
chairperson is selected as a “lead-farmer.” Lead-farmers are eligible for incentives and higher
prices for their crops based on their performance (N. Mulambya, personal communication,
August 13, 2010). Area extension officers and assistant extension officers work directly with
lead-farmers to teach conservation production practices and life skills. A regional extension
coordinator develops the curriculum for the trainings which are administered by extension staff
to the lead-farmers within their jurisdiction. After receiving this information the lead-farmers are
responsible for the education of their group members (N. Mulambya, personal communication,
August 13, 2010). The model for distributing information and collecting data was divided into
two sections.
Distributing and transferring information.
Curriculum and information is transferred through monthly trainings that each COMACO
member is required to attend in order to receive the premiums for their produce. The
information is collected in a learning tool called the Better Life Book. This book provides
written guidelines on technical methods and practices for a range of topics including
conservation farming practices, organic fertilizers, compost making, sex/HIV/AIDS, sanitation
practices, health concerns, and family values. The Better Life Book consists of a collection of
Learning Pages, each with a specific topic. Learning Pages are developed with visuals and a
minimal amount of text so they can be easily understood and applied. Learning Pages are
printed on loose sheets of heavy paper that can be added to each producer’s book. The Better
Life Book Learning Pages become a focal point of information for explaining better practices to
improve family welfare and good health while living in harmony with their environment.
COMACO trains producers in conservation farming practices that are proven methods of
increasing yields and preserving the natural habitat (B. Bunda, personal communication, August
4, 2010). Natural pesticides and fertilizers are created from plants and mulch. All COMACO
producers interviewed exhibited positive opinions about conservation practices they have been
taught. COMACO producers all claimed to realize the benefit of conservation farming from a
financial view, half of the producers claimed to realize the benefits from an environmental
standpoint, and three of the eight realized the benefits of sustainable farming. One producer
stated, “We have experienced an increase in productivity from the land and resources we use”
(104, male COMACO producer in Kakumbi). The increase in production has led the majority of
producers to claim that they would continue using conservation farming practices with or
without COMACO being present. One specific producer claimed, “Before COMACO, we had to
relocate our fields because of depleted soil. Using COMACO techniques has greatly improved
the fertility of our land and using compost as a natural fertilizer helps replenish the soil” (106,
female COMACO producer in Mnkhanya).
April 20-23, 2011
The farming practices used by the non-COMACO producers differ from practices used
by COMACO producers. Practices observed in the Jumbe area were considered to be traditional
methods of farming which can deplete the soil. Non-COMACO producers admitted to having to
create new fields after two or three years of production. Some non-COMACO producers also
claimed to burn stubble and use chemical fertilizer when affordable. A small percentage of the
non-COMACO producers interviewed recalled experimenting with a few conservation farming
practices introduced by another company that is no longer in the area.
Comparing responses from the two different groups of producers, researchers found that
the information transferred through the COMACO model is having an effect on the area.
However, researchers observed that that some of the information being transferred to producers
was inaccurate. Many COMACO producers could not explain the mission, vision, goals, or
objectives of COMACO. Only some of the producers could describe where the information
originated. When curriculum is developed and printed on Learning Pages extension staffers are
trained on the material. Extension staff is responsible for training lead-farmers who train group
leaders who train individual producers. In the line of distribution the information is often
improperly explained or misunderstood.
Collecting and recording information.
In addition to transferring information from management to the individual producers,
COMACO attempts to keep accurate records of each producer’s production practices, crop
yields, family consumption, and produce sales for each year. This information is recorded in
documents called farmer cards. Each farmer card contains data for 12 to 15 COMACO
producers. The results form lists the names and National Registration Card (NRC) numbers of
each producer in the group as well as their location. The compliance form states the overall level
of compliance for each producer. A series of individual producer forms are also included in the
farmer cards to track yields, acreage, and production for each producer (N. Mulambya, personal
communication, August 13, 2010). Group leaders are trained to evaluate the operations of the
producers in their group and record specific information as well as verify that the conservative
farming practices are being followed. The farmer cards are submitted to the regional COMACO
Trading Centre (CTC) where data is transferred to the company’s data base for analyzing and
making projections (N. Mulambya, personal communication, August 13, 2010).
Training is conducted to teach the proper methods used to record data, but written
directions are not included for group leaders. This results in team leaders and group leaders
“forgetting the proper techniques or the correct columns to record information making the entry
of data into the data bank very difficult” (G. Botha, personal communication, August 12, 2010).
The third objective sought to explore the producers’ knowledge of record keeping in
production finance. With the increased training that COMACO provides, producers now earn
enough income to sustain lifestyles without needing to rely on poaching. This has led to a
growth in the local economy and an increase in financial spending. Record keeping was not
widely evident with the COMACO farmers interviewed. Many of the producers claimed to plan
April 20-23, 2011
out what they wanted to do but it was only thought out and not written or documented. “I plan
my expenses out in my head, I don’t write anything down” (102, male COMACO producer in
Mnkhanya). Five of the eight COMACO producers interviewed had never recorded their
transactions or projected their income for any personal use. The three individuals that kept
accurate records of their operation appeared to be more progressive in their operation having
larger fields, larger storage bins, tin roofs on their homes, and a larger variety of crops. The
successful and more advanced operations kept records of transactions and budgeted their yearly
expenses and income; they also planned adequately for future investments.
Because record keeping was not a strong trend amongst the producers, finance and
savings was also a challenge. Many of the producers try to save some money to have as an
insurance base but without any documented records. More than half of the COMACO producers
interviewed claimed they found it difficult to save money. “We do not know how much
(produce) we will make or how much it will be worth so we don’t know how much money we
will get; it is hard to plan without knowing” (115, male non-COMACO producer from Jumbe).
It was difficult for producers to determine the efficiency of their cash flow. Many producers
admitted to buying items shortly after selling to COMACO without planning for future expenses.
This impulsive buying leaves producers with limited funds for major expenses later in the year.
Personal record keeping, budgeting, and financial planning were not commonly practiced
with the 13 non-COMACO producers interviewed. Only one of the 13 producers claimed to
have any knowledge of budgeting, and all 13 non-COMACO producers admitted they had never
documented any expenses or operational plans. One producer commented, “I only plan out my
expenses in my head, I am the only one farming on my land so there is no reason to write
anything down” (112, male non-COMACO producer in Jumbe). The producers were unsure of
yields, land size, and planting rates practiced in their operation throughout the year. Savings and
investments for the non-COMACO producers were difficult to gauge due to their limited income
and varying consumption rates. Because the non-COMACO producers claimed to have no
market outside of local residents, bartering for goods with produce was more common than using
money.
Conclusions and Recommendations
In order for local producers to become COMACO members and receive the premiums for
their surplus produce they must turn in their snares and muzzle loaders used for poaching to
show their commitment to a new way of living. This style of rewarding proper practices is
effective in implementing conservation farming in the area. COMACO members begin
producing enough crops to secure family consumption after one year and begin selling extra
produce for additional income after the third year. Currently, the ability of COMACO to offer
premium prices for produce and transporting its products is dependent on receiving supplemental
funding from outside sources. COMACO currently picks up raw produce in production fields
and transports these goods to a CTC for processing and packaging. COMACO then transports
the packaged product to markets where consumers have access to the commodity. COMACO
provides a market for producers to sell their extra produce. Non-COMACO producers struggle
greatly with not having a market and not having a means of transport for their goods. COMACO
April 20-23, 2011
processing increases the value of the produce. In addition, COMACO employs positions in
processing, extension, management, and transportation, creating additional income in local areas.
Researchers recommend that the current conservation farming practices be continued by
the COMACO extension staff. Also, new research in production practices should continue to be
explored. The researchers also recommend that successful producers be encouraged and
motivated to take on the responsibility of getting the product to the consumer, including
transportation and processing. Producers should organize large groups to invest in a
transportation vehicle for delivering goods from the field to a processing plant. The group could
hire the vehicle out to other producers or establish a business of transporting goods. Producers
should also establish local processing so that goods sold to COMACO are ready for packaging
and goods sold to consumers are ready for consumption. This would not only create more jobs
but also create competition to drive the market. The COMACO model appears to be effective in
enhancing food security and increasing household income for small-scale producers.
The Better Life Book is a very effective way of distributing consistent information. The
model has not been explained well to all lead-farmers and group leaders and, therefore, in some
cases is being incorrectly taught to the producers. One extension officer commented, “The level
and ability of team leaders to transfer information from lead-farmer trainings to group leaders
varies tremendously and some information never reaches the target audience” (N. Mulambya,
personal communication, August 13, 2010). In addition to distributing information efficiently,
COMACO management is concerned with keeping accurate records of their producers’ practices
and yields in their fields as well as recording data of the growth and progress of the company.
However, group leaders and team leaders do not consistently fill out the farmer cards properly
and verification of recorded details is not adequately checked for accuracy.
The researchers recommend that COMACO extension staff emphasize the importance of
the accurate transfer of information by incorporating leadership development into the curriculum
to improve the consistency of teaching. Researchers also recommend that a learning page be
added in the Better Life Book to educate the members on the structure of COMACO. This
learning page should include the following: 1) the mission and vision that guide the company; 2)
the goals and objectives that drive the company; and 3) the way information is transferred from
one level to the next. The page should also include a figure to represent the COMACO model in
which the producer should be placed at the top to promote the significance of the individual
producer. COMACO has developed an effective model for transferring knowledge from
management to small-scale producers that can be examined for promoting other extension
programs.
The researchers also recommend that farmer cards include a set of directions for group
leaders to refer to when filling in the information which includes an explanation of the purpose
and importance of the forms. Directions for the results form should emphasize the importance of
the NRC number and proper order of producers. For the compliance form, directions should
include an example of acceptable comments. A detailed example should accompany the
individual producer forms to assist group leaders while filling out the forms. Directions for all
forms should include the proper verification practices to be conducted in order to ensure proper
data is being reported to the upper management. The researchers also recommend that each lead-
April 20-23, 2011
farmer be required to check each form for accuracy and physically verify a minimum of five
producer’s operations under each group leader to ensure proper data were recorded before
submitting the farmer cards to extension staff. Additionally, the researchers recommend that
each extension staff check the forms for accuracy and physically verify a minimum of three
producer’s operations under each team leader to ensure proper data is recorded before submitting
the farmer cards to the extension coordinator. Farmer cards have been paramount in the current
success of COMACO and verification of these cards is an essential element in ensuring the
continued success of the company.
The producer’s level of knowledge in financial record keeping for production finance
varied tremendously. A common trend among successful producers was the documentation of
their personal financial budgets at the beginning of each year and forecasting expected yields.
Another common trend identified was that producers who struggle with loans often fail to plan
out expenses and producers who struggle with income often fail to plan ahead or save.
The need for financial training is essential. The researchers recommend that a learning
page be developed to highlight the importance of developing a yearly budget, documenting
transactions, and saving for large investments. The researchers recommend that all producers be
trained to keep financial records, document expected expenses, project income from produce,
plan out future investments for their operations, and establish saving plans. The Learning Page
should include examples and explanations of itemizing expenses and income, savings accounts,
and projecting income. When training on the subject, scenarios should be used to incorporate the
practices of listing out expenses and recording transactions. Documenting transactions provides
individuals with factual information on spending habits and assists in future planning of financial
investments (Ramsey, 2002).
COMACO producers reported a large variety of major challenges for their conservation
production practices. The major challenges for COMACO producers prioritized by most
frequent responses to least frequent include destruction of produce caused by wildlife, water
shortages, transporting produce, vigorous labor in conservation agriculture, and a lack of
knowledge in financial planning. The most significant challenge among non-COMACO
producers related to food production in the Luangwa Valley was wildlife destroying crops grown
for human survival. Researchers recommend that further research be conducted to identify
solutions to control wildlife while being consistent with COMACO’s mission of preserving
wildlife through sustainable agriculture.
This study is directly related to the third (Identify appropriate learning systems to be used
in nonformal education settings), fourth (Examine appropriate non-formal educational delivery
systems), and fifth (Identify and use evaluation systems to assess program impact) research
priority areas of Agricultural Education in Domestic and International Settings: Extension and
Outreach of the National Research Agenda for Agricultural Education and Communication.
April 20-23, 2011
References
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from beginning to end. Thousand Oaks, CA: Sage.
Brink, H. (1991). Quantitative vs. qualitative research. Nursing RSA, 6 (1), 14-8.
Denzin, D. K., & Lincoln, Y. S. (1994). Handbook of qualititative research. California: Sage.
Gall, M. D., Borg, W. P., & Gall, J. P. (1996). Educational Research (6th Edition). New York:
Longman.
Glesne, C. (2006). Becoming Qualitative Researchers, Third Edition. Boston: Pearson
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Hunger and Poverty. (2010, September). Community Markets for Conservation. Retrieved from
http://www.itswild.org/hunger-and-poverty
Lewis, D., & Jackson, J. (2005). Safari hunting and conservation on communal land in Southern
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San Francisco: Jossey-Bass.
Patton, M. Q. (2002). Qualitative research and evaluation methods (Third Edition). Thousand
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Poor Market Development. (2010, September). Community Markets for Conservation. Retrieved
from http://www.itswild.org/poor-market-development
Ramsey, D. (2002). Financial Peace: The Great Misunderstanding. New York: Lampo Group
Inc.
Rural Poverty Portal. (2010, September). International Fund for Agricultural Development.
Retrieved from http://www.ruralpovertyportal.org/web/guest/country/home/tags/zambia
Savin-Baden, M., & Major, C. H. (2010). New Approaches to Qualitative Research. New York:
Routledge.
April 20-23, 2011
Evaluating the Effectiveness of Traditional Training Methods in
Non-Traditional Training Programs for Adult Learners
Caleb D. Dodd, Scott Burris, Ph.D., Steve Fraze, Ph.D., David Doerfert, Ph.D, Abigail
McCulloch, M.S.
The incorporation of hot and cold food bars into grocery stores in an effort to capture a
portion of the home meal replacement industry is presenting new challenges for retail food
establishments. To ensure retail success and customer safety, employees need to be educated in
food safety practices. Traditional methods of training are not meeting the needs of the retail
food industry. Although many food safety training programs exist, few meet the educational
needs of hot and cold food bar employees. In an effort to determine the effectiveness of
traditional training methods for employees, a quasi-experimental study was performed. Data
was collected from three separate chains within the retail food industry from six geographical
locations. The pre-post assessment study utilized an interventional training and included
collecting questionnaires from 300 employees. Findings of the study described characteristics of
employees within each chain individually and collectively. Food safety knowledge was assessed
by comparing pre-training and post-training assessments for managerial and non-managerial
employees. The most important finding for this study was determining the change in essential
food safety knowledge of employees after traditional food safety training was conducted for
managerial employees within the treatment stores and comparing that change to the change that
occurred in the control groups.
Introduction-Theoretical Framework
The retail food industry is rapidly changing with new trends and practices emerging
constantly (Bolton, Shankar, & Montoya, 2010). Throughout the past decade, Home Meal
Replacement (HMR) has developed into a leading trend in the food service and grocery
industries (Quested, Cook, Gorris, & Cole, 2010). Foodservice operations are competing with
grocery stores for the traditional food market (Friddle, Mangaraj, & Kinsey, 2001). With the
HMR trend taking over the industry, grocery stores are striving to maintain their traditional hold
on the food market by developing ready-to-eat hot and cold self-service food bars (Binkley &
Ghiselli, 2005).
With the addition of new products, kitchens, and procedures comes additional food safety
concerns (Friddle et al., 2001). These concerns lead to a need to incorporate food safety training
for the new procedures. In order to provide safe food, employees need to know how to properly
prepare and maintain food for hot and cold food bars and be trained to properly use kitchen tools
and equipment (McCulloch, 2009). This new market opportunity presents a need for training to
ensure proper food safety practices in the hot and cold food bars within the grocery store
industry.
An organized approach is necessary to identify and fulfill training needs. In 2006,
organizations spent $129.6 billion dollars on training to prepare employees for conducting their
tasks. With such a sizable investment, organizations must prioritize and focus training resources
where they will be most effective (Moskowitz, 2008). One way of providing this focus is
April 20-23, 2011
through the utilization of a needs assessment. A needs assessment is the process of identifying
needs, prioritizing them, making needs-based decisions, allocating resources, and implementing
actions in organizations to resolve problems underlying important needs (Altschuld & Kumar,
2010). Moskowitz (2008) found that the most efficient way to collect data for a training needs
assessment is through surveys. However, employee behavior can also be observed in the
working environment to provide usable data for the assessment. In addition, tests can be
administered to employees to assess job knowledge (Moskowitz, 2008).
There are many methods for conducting a needs assessment. In 1984, Witkin developed
a process model that contained three phases and emphasized three levels of need (Altschuld &
Kumar, 2010). Since then, Altschuld and Kumar (2010) have revised the model.
Phase I of the needs assessment model consists of becoming organized and focusing on
potential areas of concern. This includes exploring literature and research to determine what is
already available and its level of success as it relates to the specified focus of each employer.
Phase I is a critical building block of a needs assessment as it leads to a wealth of information
about the areas of concern. The purpose of this phase is to take advantage of existing data
(Altschuld & Kumar, 2010). Previously literature of training strategies and programs within the
grocery industry was researched to complete Phase I of the needs assessment.
Phase II deals with gathering new information based on what has not been discovered in
Phase I. Phase II involves determining initial needs, prioritizing these needs, and analyzing their
possible solution strategies. Phase II often requires an extensive investment of time, personnel,
and resources for the collection of new data (Altschuld & Kumar, 2010). A pre-test/post-test
study was conducted to create a wealth of new data to complete Phase II of the needs assessment.
Designing and implementing solutions for high-priority needs and evaluating the results
of the needs assessment process constitute Phase III. Evaluation of the process generally is not
done but should be completed as part of organizational development and change (Altschuld &
Kumar, 2010). Recommendations were made for future training programs to complete Phase III
of the needs assessment.
Despite the success, there have been many challenges for grocery stores that serve
HMRs, including time, labor, and food safety risks. The intricate food structure, employee
turnover, and food pathogens are hampering the safety efforts that supermarkets utilize in the
United States (Binkley & Ghiselli, 2005). Even if perfect production and distribution practices
are followed, consumers may not follow safe-handling procedures (Reyes, 2002). This
knowledge combined with the fact that many grocery stores are adding kitchens and unfamiliar
equipment and processes to their businesses forces grocery stores to be more focused on food
safety practices and train their employees to handle food safely (Binkley & Ghiselli, 2005).
Effective food safety plans and well-trained staff can help prevent an unwanted outbreak
of foodborne illness. As the complexity of the food distribution and retailing system increases,
the need for more stringent food safety controls and training increases as well. Food safety
training and certification are a crucial part of any food safety plan (Drummer, 1998).
Implementing an effective food safety training program for employees, applying a sanitation
April 20-23, 2011
program, and designing a crisis plan in the case of a foodborne illness outbreak are evident needs
in the HMR market (Binkley & Ghiselli, 2005).
There are many barriers to implementing effective food safety training for employees. A
small staff base, employee turnover, lack of time, cost, a lack of suitable courses, and
inflexibility of courses were reported as the most common barriers when attempting to provide
effective training for supermarket employees (Worsfold, 2005). Some researchers suggest that
food safety training is effective, but others find no improvement in food safety practices after
training employees (York et al., 2009).
Worsfold (2005) found that effective training did not appear to be on the agenda of
priorities for many food managers. Some managers in the study viewed training as an operating
expense and did not realize the benefits. Due to low cost and convenience, on-the-job training
was the most common type of training within the food service industry (Worsfold, 2005). This
type of training can produce negative results including poorly trained employees who use
dangerous or ineffective methods to produce food products (Worsfold, 2005).
The purpose of this study was to determine the effectiveness of commonly used training
methods within a non-traditional learning program. Food safety is a major concern that is
continually faced by grocery stores and other food providers (Binkley & Ghiselli, 2005). Food
workers’ improper preparation procedures are the most prominent cause of foodborne illness
outbreaks (Foodborne Illness, 2010). Effective training is needed to allow for grocery store
employees to prepare and serve food in a manner that is safe and foodborne illness free.
This study is directly related to the fourth (Examine appropriate non-formal educational
delivery systems) and fifth (Identify and use evaluation systems to assess program impact)
research priority areas of Agricultural Education in Domestic and International Settings:
Extension and Outreach of the National Research Agenda for Agricultural Education and
Communication. In order to successfully complete this study, objectives were determined to
identify the effectiveness of traditional training methods within stores by transferring knowledge
from managerial employees to non-managerial employees. This needs assessment was guided
by two research objectives:
1. Describe characteristics of managerial and non-managerial individuals employed
within the hot and cold self-service food bars of grocery stores.
2. Access the change in food safety knowledge of stores between pre-assessment and
post-assessment.
The research design for this study was quasi-experimental. This type of experiment lacks
random assignment but can yield useful knowledge if it is carefully designed (Gall, Gall, &
Borg, 2007). The study contained an education intervention. Initial assessment was pre-test,
followed by a traditional food safety training program, then followed by a post-test assessment.
The effectiveness of the training program and the transfer of information from managerial
April 20-23, 2011
employees to non-managerial employees were determined through differences in the pre-training
questionnaires and post-training questionnaires.
With the intention of developing a computer-based training program for hot and cold
self-service food bars in the grocery store industry, the United States Department of Agriculture
(USDA) funded a research grant through the International Center for Food Industry Excellence
(ICFIE). Three grocery chain retail food providers agreed to participate in the collaborative
project. The chains span six geographical regions within five states. In order to properly assess
the effectiveness of food safety training it was determined that both managerial and nonmanagerial employees should be included in the study. The target population included
employees that worked in the hot and cold self-serve food bar department of grocery stores. The
sampling technique used for this study was non-probabilistic purposive.
The grocery chains agreed to allow one managerial employee and two non-managerial
employees to complete a written questionnaire. Following the initial data collection period,
managerial employees from randomly selected stores participated in an interventional food
safety training program presented in a traditional classroom method. The stores not selected
were identified as a control group, while the stores participating in the training were identified as
the treatment group. The interventional food safety training the managerial employees received
was presented by professionals using certification curriculum. Post-training data was collected
no less than 30 days later, this period of time gave managerial employees time to transfer new
knowledge to non-managerial employees within the stores. Post-training data included the same
questionnaire, again targeting one managerial employee and two non-managerial employees.
After the collection of the data, analysis was performed to identify what effects the training had
on the stores’ food safety knowledge collectively.
The accessible sample for the needs assessment consisted of 44 stores from three grocery
chains in five states who offered hot and cold self-service food bars for customers. The 44 stores
were represented by 300 questionnaires. Fifty-six managerial employees and 113 nonmanagerial employees participated in the pre-assessment of food safety knowledge, whereas 43
managerial employees and 88 non-managerial employees participated in the post-training
questionnaire. The sampling technique was non-probabilistic. Results of this study cannot be
generalized to a larger population due to the fact that the sample was purposively selected by the
chains upper management. However, the sampling technique does allow for adequate needs
assessment to be performed.
The instrument used for this study was a Food Safety Questionnaire developed for a preassessment to develop a food safety training program (McCulloch, 2009). The questionnaire
consisted of five sections. The questionnaire was developed in both English and Spanish. As
reported by McCulloch, the content and validity of the instrument used for this study was
established by a panel of experts. McCulloch reported the Kuder-Richardson 20 coefficient was
0.51. This is relatively low, but acceptable value for the Kuder-Richardson (Nunnally, 1967).
Two different modes were used for collecting data from employees. An online
instrument was initially developed for the delivery of the questionnaire; a paper booklet was then
designed to accommodate individuals without access to internet connections. The collection of
pre-test and post-test data spanned 15 months. The study was designed to offset data collection
April 20-23, 2011
between chains to reduce the number of personnel used data collection. Data from each chain
was collected within a 200-day period.
Data was entered and analyzed using the Statistical Package for Social Sciences (SPSS)
16.0 computer program for Microsoft Windows. Microsoft Excel 2007 was used for calculating
scores. Descriptive data for objective one was reported using frequencies, percentages, means,
and standard deviations. In analyzing data for objective two, 16 questions from section two of
the questionnaire were used to determine food safety knowledge scores. Each participant
received a percentage score representing the number of questions the individual answered
correctly out of the 16 possible. Objective two assessed the change between pre-training food
safety knowledge and post-training food safety knowledge of employees.
Findings
Managerial employees’ data was analyzed separately from non-managerial employee
data as statistical comparison between the two groups was not suitable. The findings are
presented by each chain individually and from all stores cumulatively. Table 1 provides a
summary of the number of participants by chain for each phase of data collection.
Table 1
Summary of Number of Participants by Employment Type, Location, and Administration
Participants (N)
Chain I
Chain II
Chain III
Cumulative
Stores
Control Group
9
7
8
24
Treatment Group
6
8
6
20
Total
15
15
14
44
Managerial Employees
Pre-Training Control
8
9
12
29
Post-Training Control
9
12
6
27
Pre-Training Treatment
8
10
9
27
Post-Training Treatment
5
9
2
16
Total
30
40
29
99
Non-managerial Employees
Pre-Training Control
23
16
18
57
Post-Training Control
20
17
11
48
Pre-Training Treatment
23
16
17
56
Post-Training Treatment
11
18
11
40
Total
77
67
57
201
Objective one sought to describe the employees participating in the study. This section
described the demographic characteristics of the participants along with their retail food
experience and experiences in food safety training. The average age of the participants and their
average number of years in the retail food industry are presented in Table 2. The mean age of
managerial employees in the study was 39 (SD=9.2) while non-managerial employees’ average
age was slightly younger (M=38) with a higher level of variance (SD=13.8). The average
number of years in the industry for managerial employees was 10 years (SD=7.0). The average
for non-managerial employees in the retail food industry was six years (SD=6.2).
April 20-23, 2011
Table 2
Participants’ Ages and Years of Experience
Chain I
Characteristic
M
SD
Managerial Employees
Age
41
10.6
Years in Industry
8
8.4
Non-managerial Employees
Age
39
16.4
Years in Industry
5
6.1
Chain II
M
SD
Chain III
M
SD
Grand Mean
M
SD
40
11
8.9
7.2
36
10
7.7
4.4
39
10
9.2
7.0
36
6
12.7
6.7
40
7
10.8
5.4
38
6
13.8
6.2
Gender, current positions held, and levels of education for the managerial employees are
reported in the Table 3. Just over half the managerial employees were female (n=50). Fifty-five
percent (n=55) of managerial employees in the study reported being their stores’ department
manager. The level of education of the managerial employees varied from 21.2% of participants
(n=21) reporting having some high school to 11.1% of participants (n=11) having earned a
bachelor’s degree. Almost half of the managerial employees reported either a high school
diploma or some high school being their highest level of education.
Table 3
Managerial Employees’ Gender, Position, and Education Level
Chain I
Chain II
Characteristic
f
%
f
%
Gender
Female
14
46.7
26
65.0
Male
13
43.3
14
35.0
Undisclosed
3
10.0
0
0.0
Position
Department Manager
19
63.3
22
55.0
Department Head
2
6.7
4
10.0
Co-Manager
3
10.0
2
5.0
Other title
6
20.0
12
30.0
Education
Some High School
10
33.3
9
22.5
High School Diploma
5
16.7
12
30.0
Some Culinary/Tech
6
20.0
3
7.5
Graduate Culinary/Tech
2
6.7
4
10.0
Associate’s Degree
5
16.6
6
15.0
Bachelor’s Degree
2
6.7
6
15.0
Chain III
f
%
Cumulative
f
%
10
18
1
34.5
62.1
3.4
50
45
4
50.5
45.5
4.0
14
5
2
8
48.3
17.2
6.9
27.6
55
11
7
26
55.6
11.1
7.1
26.2
2
8
4
1
11
3
6.9
27.7
13.8
3.4
37.9
10.3
21
25
13
7
22
11
21.2
25.3
13.1
7.1
22.2
11.1
The same information provided for managerial employees in Table 3 was provided for
non-managerial employees in the study in Table 4. Unlike the managerial employees, who were
relatively even in the female-to-male ratio, females accounted for 68.1% (n=137) of all the nonmanagerial employees participating in the study. Although 21.4% (n=43) of the non-managerial
employees reported holding positions with titles, the vast majority, 78.6% (n=158) reported
being an hourly employee or some other title. The level of education did fluctuate from
percentages reported by managerial employees. However, the most frequent responses remained
April 20-23, 2011
the same with 65 (32.3%) of the non-managerial employees reporting a high school diploma as
the highest level of education and some high school accounting for 28.9% (n=58).
Table 4
Non-managerial Employees’ Gender, Position, and Education Level
Chain I
Chain II
Chain III
Characteristic
f
%
f
%
f
%
Gender
Female
52
67.5
46
68.7
39
68.4
Male
20
26.0
20
29.9
17
29.8
Undisclosed
5
6.5
1
1.5
1
1.8
Position
Shift Leader
3
3.9
12
17.9
7
12.3
Department Head
2
2.6
0
0.0
2
3.5
Assistant Head
5
6.5
8
11.9
4
7.0
Hourly Employee
61
79.2
44
65.7
29
50.9
Other title
6
7.8
3
4.5
15
26.3
Education
Some High School
27
35.0
18
26.9
13
22.8
High School Diploma
23
29.9
26
38.8
16
28.1
Some Culinary/Tech
15
19.5
10
14.9
9
15.8
Graduate Culinary/Tech
3
3.9
3
4.5
2
3.5
Associate’s Degree
5
6.5
7
10.4
9
15.8
Bachelor’s Degree
4
5.2
3
4.5
8
14.0
Cumulative
f
%
137
57
7
68.1
28.4
3.5
22
4
17
134
24
10.9
2.0
8.5
66.7
11.9
58
65
34
8
21
15
28.9
32.3
16.9
4.0
10.4
7.5
Methods of training received and time spent training for managerial employees are
displayed in Table 5. When responding to methods of training received, participants were
encouraged to answer all that applied to their individual experience.
Table 5
Managerial Employees’ Experience with Food Safety Training
Chain I
Chain II
Characteristic
f
%
f
%
Method of Training
Classroom
17
56.8
39
97.5
On-the-job
20
66.7
15
37.5
Textbook
8
26.7
11
27.5
Video
9
30.0
15
37.5
Computer-based
24
80.0
2
5.0
Company-web
10
33.3
0
0.0
Internet
6
20.0
0
0.0
Time Spent Training
More than 3 days
12
40.0
4
10.0
2 – 3 days
7
23.3
24
60.0
1 day
3
10.0
2
5.0
6 – 12 hours
3
10.0
6
15.0
Less than 5 hours
5
16.7
4
10.0
April 20-23, 2011
Chain III
f
%
Cumulative
f
%
26
10
17
11
3
3
1
89.7
34.5
58.6
37.9
10.3
10.3
3.4
82
45
36
35
36
13
7
82.8
45.5
36.4
35.4
29.3
13.1
7.1
2
21
4
1
1
6.9
72.4
13.8
3.4
3.4
18
52
9
10
10
18.2
52.5
9.1
10.1
10.1
Classroom training, accounting for 82.8% (n=82), was the most common method
reported by managerial employees. It was also the most frequent response in two of the three
chains. Eighty percent of managerial employees (n=24) in Chain I reported computer-based
training to be most prominent. Only two managerial employees (5.0%) in Chain II and three
managerial employees (10.3%) in Chain III reported utilizing computer-based training.
Although city and state certification appeared to be the most popular training certification with
48.8% (n=49), it was less than half of the most frequent response in two of the three chains.
Fifty-two managerial employees (52.5%) reported spending between two and three days in food
safety training. Two to three days training was also the majority in Chain II and Chain III;
however, 40% (n=12) of managerial employees in Chain I reported spending more than three
days in food safety training. Methods of training and time spent training for non-managerial
employees are described in Table 6.
Table 6
Non-managerial Employees’ Experience with Food Safety Training
Chain I
Chain II
Chain III
Characteristic
F
%
f
%
f
%
Method of Training
Classroom
13
16.9
51
76.1
40
70.2
On-the-job
53
68.8
44
65.7
38
66.7
Textbook
15
19.5
11
16.4
31
54.4
Video
34
44.2
25
37.3
31
54.4
Computer-based
46
59.7
1
1.5
12
21.1
Company-web
13
16.9
1
1.5
11
19.3
Internet
3
3.9
2
3.0
3
5.7
Time Spent Training
More than 3 days
12
15.6
7
10.4
7
12.3
2 – 3 days
11
14.3
22
32.8
24
42.1
1 day
14
18.2
11
16.4
9
15.8
6 – 12 hours
2
2.6
7
10.4
8
14.0
Less than 5 hours
38
49.3
20
30.0
9
15.8
Cumulative
f
%
104
135
57
90
59
25
8
51.7
67.2
28.4
44.8
29.4
12.4
4.0
26
57
34
17
67
12.9
28.4
16.9
8.5
33.3
Unlike the responses given by the managerial employees, the method of training most
frequently used, as reported by non-managerial employees, was on-the-job training by 67.2%
(n=135). Chain II and Chain III aligned more closely to the numbers reported by managerial
employees. The most frequent method of training for these chains was classroom training by
76.1% (n=51) for Chain II and 70.2% (n=40) for Chain III. At 59.7% (n=46), more than half of
Chain I non-managerial employees reported participating in computer-based training. Like
managerial employees from Chain II and Chain III, only one non-managerial employee from
Chain II (1.5%) and 12 non-managerial employees from Chain III (21.1%) reported using
computer-based training. The amount of time spent training also differed from responses given
by managerial employees. The most frequent response given by non-managerial employees was
less than five hours with 33.3% (n=67). Two to three days was the second most frequent overall
and the most frequent in Chain II with 32.8% (n=22) and Chain III with 42.1% (n=24).
Objective two assessed the change in food safety knowledge of employees from the preassessment to the post-assessment. Food safety knowledge was assessed through 16 multiple
April 20-23, 2011
choice items developed specifically to test the essential knowledge of employees within the hot
and cold self-service food bar sectors of grocery stores. Each participant was given a score
based on the percentage of items they answered correctly out of the 16 questions. Scores were
averaged among the control groups and treatment groups for both pre-training and post-training
assessments for each chain individually and cumulatively. Changes in scores were calculated for
each category of participants.
The difference in percentage scores were used for comparing and identifying changes
between pre-training and post-training performance. There are many different levels of pretraining food safety knowledge scores reported in this section. Knowledge scores that are high in
the pre-training assessment do not leave as large of a window for improvement to occur.
Identifying the changes in scores allowed researchers to compare and contrast but should not be
the only way of measuring effectiveness.
The food safety knowledge scores for managerial employees are reported in Table 7. The
scores are reported as an average of the percentage of correct answers of all the managerial
employees in each category identified in the study. The difference in the pre-training and posttraining scores represents the change in food safety knowledge that occurred over time between
the collections of the data. The control group received no additional treatment between the
assessments of knowledge, whereas managerial employees in the treatment group participated in
interventional training for food safety.
Table 7
Change in Food Safety Knowledge Scores for Managerial Employees
Chain I
Chain II
Chain III
Knowledge
C
T
C
T
C
T
Pre-Training
68.8
68.0
81.3
83.8
65.6
70.9
Post-Training
70.8
75.0
79.2
81.3
77.1
81.3
Difference in Scores
2.0
7.0
(2.1) (2.5) 11.5
10.4
Note. C=Control Group, T=Treatment Group
Cumulative
C
T
71.3
74.8
75.9
79.3
4.6
4.5
Cumulatively, the control group had lower pre-training (71.3%) and post-training
(75.9%) scores than the treatment group (74.8%, 79.3%). However, the difference in the amount
of change that occurred over time between both groups was one-tenth of a percent. Chain I’s
pre-training scores were extremely close (68.8%, 68.0%), but a 7.0% increase occurred in the
treatment group as opposed to the 2.0% increase that was seen in the control group between the
pre-training and post-training assessments of knowledge. Chain II had the highest scores by far
on the assessment prior to training with the control group scoring 81.3% and the treatment group
scoring 83.8%. Chain II also had a negative change in knowledge with both groups dropping in
their average scores by 2.1% (control) and 2.5% (treatment). Although Chain II had a decrease
in scores, the percentage of correct answers on the post-training assessment remained the top
scores represented in the data (79.2%, 81.3%). Chain III’s control group started with the lowest
score of 65.6%, but had the largest change of 11.0%. Chain III’s treatment group also had an
increase in knowledge from 70.9% (pre-training) to 81.3% (post-training) for a change of 10.4%.
The food safety knowledge scores for non-managerial employees are reported in Table 8.
The difference in the pre-training and post-training scores represents the change in food safety
April 20-23, 2011
knowledge that occurred over time between the collections of the data. The managerial
employees in the control group received no additional treatment between the assessments of
knowledge; whereas, the managerial employees in the treatment group participated in
interventional food safety training. Non-managerial employees received no additional training.
Table 8
Change in Food Safety Knowledge Scores for Non-managerial Employees
Chain I
Chain II
Chain III
Knowledge
C
T
C
T
C
T
Pre-Training
62.8
59.0
75.0
71.5
63.5
58.8
Post-Training
67.8
66.5
68.0
65.3
61.4
60.1
Difference in Scores
5.0
7.5
(7.0) (6.2) (2.1)
1.3
Cumulative
C
T
67.2
62.5
66.4
64.2
(0.8)
1.7
The average knowledge scores for non-managerial employees were lower than the scores
reported for managerial employees across the board. Cumulatively, the non-managerial
employees pre-training scores were 67.2% for the control group and 62.5% for the treatment
group. A slight decrease of 0.8% was scored on the post-training score in the control group with
a slight increase of 1.7% occurring in the treatment group. Chain I was only 0.2% away from
having the lowest scores on the pre-training assessment and only 0.2% away from having the
highest scores on the post-training assessment. Chain I had the greatest amount of change for
both the control group (5.0%) and the treatment group (7.5%). Chain II had the highest scores
on the pre-training assessment (75.0%, 71.5%) but, like the managerial employees, also showed
the greatest decrease in knowledge scores (7.0%, 6.2%). Even with the decrease in knowledge
scores, the non-managerial employees in Chain II had some of the highest scores recorded in the
post-training assessment. Chain III’s non-managerial employees showed the least amount of
change from pre-training to post-training assessments. The control group’s score decreased
2.1% while the treatment group’s score increased by 1.3%.
A comparison of food safety knowledge percentage scores between managerial and nonmanagerial employees was conducted to assess the difference in food safety knowledge between
the two groups. The pre-training and post-training food safety knowledge percentage scores are
displayed in Table 9.
Table 9
Difference in Food Safety Knowledge Scores for Different Types of Employees
Chain I
Chain II
Chain III
Knowledge
C
T
C
T
C
T
Pre-Training
Managerial
68.8
68.0
81.3
83.8
65.6
70.9
Non-managerial
62.8
59.0
75.0
71.5
63.5
58.8
Difference
6.0
9.0
6.3
12.3
2.1
12.1
Post-Training
Managerial
70.8
75.0
79.2
81.3
77.1
81.3
Non-managerial
67.8
66.5
68.0
65.3
61.4
60.1
Difference
3.0
8.5
11.2
16.0
15.7
21.2
April 20-23, 2011
Grand Mean
C
T
71.3
67.2
4.1
74.8
62.5
12.3
75.9
66.4
9.5
79.3
64.2
15.1
The average scores for managerial employees in every chain was consistently higher that
the non-managerial employees’ scores. In the pre-training, Chain II had the highest scores for
both managerial and non-managerial employees, but also had the largest difference in scores
with 6.3% in the control group and 12.3% in the treatment group. The difference in food safety
knowledge scores was consistently larger in the treatment groups for the pre-training assessment.
The difference of food safety knowledge scores between the managerial and non-managerial
employees grew larger in every group except Chain I’s control group from the pre-training to the
post-training. The gap of knowledge grew the largest in Chain III. The control group had a
2.1% difference in the pre-training and a 15.7% difference in the post-training while the
treatment group went from a 12.1% difference in the pre-training to a 21.2% difference in the
post-training. The overall increase in the difference in food safety knowledge scores between the
managerial and non-managerial employees was 5.4% (control) and 2.8% (treatment).
Conclusions-Implications-Recommendations
The employees in this study reported a similar average age. This is most likely due to the
high population of high school students mixed with the growing number of baby boomers
reaching retirement age and taking part-time employment in the retail food service industry to
supplement retirement funds. Managerial employees had almost twice as many years of
experience in the industry than did non-managerial employees. This represents two important
aspects. First, time in the industry is an important factor for promotion and career success within
the industry. Second, non-managerial employees who stay in the industry for an extended period
of time are likely to move into management positions. Because non-managerial employees are
the ones who move into the management positions, training should be focused on all employees,
not only managerial employees.
Most managerial employees in the study held positions with titles and reported a variety
of educational levels from some who had only attended some high school to others who had
earned bachelor degrees. The majority of non-managerial employees were on hourly
employment with over 60% reporting either a high school diploma or some high school. There
is a large intellectual range of participants targeted for food safety training. This finding is
consistent with findings from McCulloch (2009).Over half of all the employees who participated
in the study reported their highest level of education to be a high school diploma or some high
school. Based on this finding, food safety training should target a junior high reading level.
Trends for methods of training and time spent training between managerial and nonmanagerial employees showed some similarities. Employees are accustomed to classroom and
on-the-job training between two and three days. This supports findings by Kramer and Scott
(2004), Worsfold (2005), and York et al., (2009). Based on results of food safety knowledge
scores and number of non-managerial employees who only reported receiving on the job
training, researchers can conclude that the current methods of training are not meeting the needs
of the hot and cold self-service food bars, therefore, a more effective method for training
employees in the retail food industry is needed.
Food safety knowledge scores prior to the interventional training were compared to the
food safety knowledge scores following the training to assess the effects the interventional
training had on employees’ food safety knowledge. The average food safety knowledge scores
for employees in the post-training assessment for the treatment groups were lower than one
April 20-23, 2011
might expect on an assessment of essential knowledge. This finding was consistent with the
results of other food safety studies conducted by Hertzman and Barrash (2007) within other
regions of the retail food industry. Managerial employees’ scores resulted in a 79% average, and
carried into a 64% average for their non-managerial employees. The method of transferring
knowledge to employees does not sufficiently educate participants in food safety knowledge that
is necessary to ensuring food safety for hot and cold self-serve food bar sectors of grocery stores.
The average scores for the three chains cumulatively did not exhibit a large variance
between the control group and the treatment group from pre-training to post-training.
Managerial employees’ difference was less than a tenth of a point and non-managerial
employees’ resulted in a difference of two and a half percentage points. Overall, the control
groups showed a similar change in food safety knowledge as the treatment groups in the study.
The traditional method of food safety training did not appear to effectively meet the educational
needs of employees in the hot and cold food bars.
In addition, following the training the difference in food safety knowledge between
managerial and non-managerial employees grew larger. Managerial employees were the only
ones to receive the interventional training with expectations of taking the information back to the
non-managerial employees. Information from the interventional training did not appear to have
been distributed from the managerial employees to the non-managerial employees in an effective
manner. Traditional methods of “training the trainer,” expecting information to filter down, does
not meet the educational needs within the hot and cold self-service food bar to ensure safe food
for consumers.
Food safety knowledge within the grocery store industry is not at an appropriate level to
meet the needs of food safety standards. McCulloch (2009) recommended that the most
common methods of training, classroom and on-the-job training, be utilized to build these scores.
Researchers in this study do not see these methods meeting the need and recommend that a more
effective style of training be explored to promote the retention of understanding of the concepts
and importance of food safety in hot and cold food self-service food bars of grocery stores.
Palvia and Palvia (2007) found that all methods of computer-based instruction led to an
improvement in the skills of the participants. Macaulay and Pantazi (2006) discovered that
students who used computer-based training scored significantly higher than those who used
traditional methods. Van Gerven, Paas, and Tabbers (2006) found that computer-based training
plays an important role in optimizing the level of cognitive load an individual is capable of
processing. Based on findings of this study, computer-based curriculum will be a new method
for more than half of participants. Future food safety training should utilize computer-based
instruction.
This study identified a flaw in the traditional method of training employees in the hot and
cold food bars utilizing food safety training developed for grocery stores as a whole. The study
also found that managerial employees’ food safety knowledge is not effectively distributed to
their non-managerial employees. All employees who work in any aspect of the hot and cold selfservice food bars within the grocery stores should be required to participate in additional food
safety training that focuses specifically on issues relating to hot and cold food bar food safety.
April 20-23, 2011
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Hertzman, J., & Barrash, D. (2007). An assessment of food safety knowledge and practices of
catering employees. British Food Journal, 109 (7), 562-576.
Kramer, J., & Scott, W. G. (2004). Food safety knowledge and practices in ready-to-eat food
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Macaulay, M., & Pantazi, I. (2006). Material difficulty and the effectiveness of multimedia in
learning. International Journal of Instructional Media, 33 (2), 187-195.
McCulloch, A. (2009). A preassessment for developing a food safety training program for self
service food bars in grocery stores (Unpublished masters thesis). Texas Tech University,
Lubbock, TX.
Moskowitz, M. (2008). A Practical Guide to Training and Development. San Francisco, CA:
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Quested, T. E., Cook, P. E., Gorris, L. G., & Cole, M. B. (2010). Trends in technology, trade,
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April 20-23, 2011
Exploring the Teaching Ability Views of Agricultural Education Student Teachers
Sheyenne Krysher, J. Shane Robinson
Abstract
The purpose of this study was to describe the views student teachers in agricultural education at
Oklahoma State University had regarding their 12-week student teaching experience, using Qmethodology. Three factors produced from the Q-method factor analysis represented the three
distinct views found in the sample population. The three views were the Emerging Teacher, the
Self-Assured Teacher, and the Determined Teacher. The Emerging Teacher view recognized
areas needed for growth and development but also recognized their development toward
becoming a professional. The Self-Assured Teacher view had a high level of comfort and
confidence in their teaching ability, which extended to their views on developing lessons and
teaching across the agricultural education curriculum. The Determined Teacher view recognized
confidence but not comfort in their teaching ability. Teaching did not always come easy for them,
but they recognized they were getting better.
Student teaching is one of the most commonly and widely used components in the teacher
preparation process nationally (Carnegie Forum’s Task Force, 1986). It is a culminating
internship which provides experiential learning and is “the most crucial [of] activities”
(Schumann, 1969, p. 159) during the preparation process. The student teaching internship
exposes a student teacher to the same experiences he/she will encounter as a full-time teacher
including activities both in and out of the classroom. In addition to the time spent planning and
delivering instruction, a teaching experience “involves reteaching, providing multiple
meaningful activities for diverse groups of students, managing behaviors, bookkeeping,
management, organization, traffic flow, collecting and distributing materials, and more”
(Spooner, Flowers, Lambert, & Algozzine, 2008, p. 268). Further, in regard to the preparation of
instruction, a teacher may need to plan for diverse curriculum within his/her content area. In
agricultural education for example, a teacher must instruct courses such as animal science,
horticulture, agribusiness, and agricultural mechanics (Robinson, Krysher, Haynes, & Edwards,
2010).
Time and experience are central to the growth and development of student teachers (Spooner et
al., 2008). However, as graduation requirements are decreased to under 128 credit hours,
exposing pre-service agricultural education students to real-life challenges becomes a daunting
task (Burris, Robinson, & Terry, 2005). The reduction in graduation hours limits the amount of
time available to provide vital learning experiences to future teachers. The lack of potential
learning experiences could lead to lower levels of student proficiency, which could then lead to
teachers’ levels of confidence or self-efficacy related to their teaching being diminished.
Self-efficacy is the belief one has in his/her ability successfully accomplish a specific task and is
an essential part of the human functioning given the inputs of personal behavior, cognitive
processes, and environment (Bandura, 1986). “People guide their lives by their beliefs of
personal efficacy” (Bandura, 1997, p. 3). And, self-efficacy beliefs can influence daily life,
1
April 20-23, 2011
individuals can form self-efficacy beliefs regarding specific domains or contexts such as
teaching. Tschannen-Moran, Hoy & Hoy (1998) provided an definition of teaching efficacy as, a
person’s “belief in his or her capability to organize and execute courses of action required to
successfully accomplish a specific teaching task in a particular context” (p. 233).
Though the experiences during the student teaching internship will vary from person to person, it
is through these experiences that they gain information about their teaching performance.
Bandura (1986, 1997) describes four main sources by which efficacy is built: mastery
experiences, vicarious experience, social persuasion, and physiological and emotion state.
Mastery experiences are particularly influential to student teachers through the practice of
teaching, while vicarious experiences are also influential through the observations of model or
expert teachers. Social persuasion involves the formation of efficacy beliefs through others’
suggestions about a person’s performance. A person’s efficacy also may be affected by his/her
emotional or physical state, that is, stress, fear, and anxiety may influence a person’s
vulnerability thereby lowering the appraisal of efficacy.
Self-efficacy, regarding an individual’s perception about his/her teaching ability is an important
phenomenon to understand because “once efficacy beliefs are established, they appear to be
somewhat resistant to change” (Tschannen-Moran et al., 1998, p. 235). As such, it is important to
assess student teacher self-efficacy while these individuals are still at the pre-service level
(Korthagen & Kessels, 1999) so that efforts can be made to improve the preparation they
encounter during their teaching practice experiences (Parajes, 1992). “Helping teachers develop
strong efficacy beliefs early in their career will pay lasting dividends” (Tschannen-Moran et al.,
1998, p. 234).
Though teacher efficacy is a powerful construct, it has been difficult to measure (TschannenMoran and Hoy, 2001). Several methods of measuring efficacy have been employed over the
years from the two-item scale used in the Rand Corporation studies (Armor et al., 1976; Berman,
McLaughlin, Bass, Pauly, & Zellman et al., 1977) to the 24-item scale used in the Teachers’
Sense of Efficacy Scale (Tschannen-Moran et al., 1998). However, people make judgments
about their capabilities without a clear task or activity in mind; thus, self-efficacy instruments
often suffer from “mismeasurement.” Bandura (1997) warned that instruments with few
measurements are too global and instruments that are too specific become less generalizable.
Efficacy measurements should be a balance between task and domain specific assessment
(Bandura, 1997). Other researchers have suggested that employing a variety of research methods,
including qualitative inquiry, would serve to enrich the understanding of teacher efficacy
(Henson, 2002; Tschannen-Moran et al., 1998).
Due to the need to measure self-efficacy both quantitatively and qualitatively, Q-methodology
appears to be a logical approach. Q-methodology is a qualitative research method with
quantitative features (Watts & Stenner, 2003), which might serve to study teacher efficacy
through means that have been overlooked previously. It has been recommended that, “selfefficacy beliefs should be assessed at the optimal level of specificity that corresponds to the task
being assessed and the domain of functioning being analyzed” (Pajares, 1996, p. 547). Q-method
seeks to interrogate the phenomenon holistically by allowing participants to model their
preferences in a Q-sort. (Brown, 1980).
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Purpose and Research Question
The purpose of this study was to describe the views student teachers in agricultural education at
Oklahoma State University had regarding their 12-week student teaching experience. To
accomplish this purpose, this study explored the perceptions of agricultural education student
teachers in the spring and fall semester of 2009 regarding aspects of self-efficacy. The research
question was: What views did agricultural education student teachers have about their teaching
ability?
Methodology
The theoretical structure of this study was based largely on Bandura’s self-efficacy theory
(1993). Bandura’s work on self-efficacy (1997) describes extensively how an individual’s
perceptions of his or her ability is self-referent. “Q-studies, from conception to completion,
adhere to the methodological axiom that subjectivity is always self-referent” (McKeown &
Thomas, 1988, p. 12). Specifically, subjectivity is the communication of a person’s viewpoint,
and self-reference is a person’s internal frame of reference (McKeown & Thomas).
Q-methodology was developed originally by William Stephenson in the 1930s as a research
method to study human subjectivity systematically. The quantitative portion of Q-methodology
is an adaptation of a factor analysis (Watts & Stenner, 2005) and provides researchers a
systematically method to study a person’s viewpoint, attitude, and/or belief on a chosen topic
(Brown, 1993). Unlike other correlational measurements, in which data are often gathered from
opinion questionnaires with standardized scales (Robbins, 2005), Q-methods allows for the items
to interact (Brown, 1980). In Q-method research, when a person ranks statements, he/she is rankordering each statement in comparison to one another, not evaluating the independent statements
individually. As the Q-sort is performed, the individual decides what is and is not meaningful
from his/her perspective as opposed to rating the scale items in conventional instruments, which
have predetermined meaning from the researcher (Watts & Stenner, 2005).
The participants for this study consisted of 28 student teachers in agricultural education who
were enrolled in a student teaching course in Agricultural Education at Oklahoma State
University during the spring and fall semesters of 2009. Data were collected during the
observational site-visits made by the university supervisors to the cooperating center in which
the student teacher was interning; however, some data were collected at the university. The Qsort was completed by each student teacher during weeks nine through 12 of the student teaching
internship.
The Q-set is a group of statements presented to the participants for rank-ordering (McKeown &
Thomas, 1988) and is representative of several aspects or viewpoints of a topic (van Exel & de
Graaf, 2005). This study used a combination, or hybrid approach, involving both naturalistic and
theoretical types. A total of 36 statements were used to develop the Q-set. Of those, 30 originated
from a validated instrument, The Teaching Ability Questionnaire (Spooner et al., 2008). In order
to provide breadth to the Q-set, six additional naturalistic statements were added, based on
informal discussions and debriefings with several semesters of student teachers. As such, the
additional six statements focused on the concerns student teachers anticipated upon arriving at
the cooperating center such as locating, developing, and teaching curriculum in multiple
agricultural education subjects, i.e., animal science, horticulture, agricultural mechanics, and
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April 20-23, 2011
agribusiness. In total, all the statements represented multiple roles of teacher performance, which
should reveal the participants’ perception of their teaching ability accurately.
Each statement in the Q-set was printed onto a piece of cardstock and presented to the student
teachers for sorting, i.e., rank-ordering. The rank-ordering of the statements was in response to a
condition of instruction (prompt) which the participants formulate an opinion (Brown, 1993).
The condition of instruction for this study was, “How do you feel about the courses you
instruct?”. After the condition of instruction was presented to the students, they began to rankorder each statement of the Q-set. To begin the process, each student read every statement and
determined how it represented his or her feelings about the courses they instructed. Student
teachers were instructed to sort the Q-statements into three distinct piles. The first pile contained
statements that participants believed represented how they felt about the courses they taught. The
second pile contained statements they did not believe represented their feelings about the courses
they taught. The third pile contained statements in which they felt neutral regarding the courses
they taught.
After all the statements had been placed into one of the three piles, the cards were then
distributed onto a Q-sort Form Board. The form board was constructed with a distribution range
of nine columns. Each column was assigned a ranking value from -4 to +4 (Figure 1).
Most
unlike me
-4
-3
-2
-1
0
+1
+2
+3
+4
Most
like me
Figure 1. Q-sort Form Board
The two statements in which the student teachers believed were most like them were placed on
the extreme right side of the distribution (+4), and the two statements the student teachers
believed were most unlike them were placed on the extreme left side (-4) of the distribution. The
process was repeated working toward the middle row (0) until all cards were placed on the board
by each student teacher. The statements placed in the middle row consisted of statements in
which the student teacher felt neutral. Finally, the placement of the statements was recorded onto
the response sheet by the student teacher for data analysis. Space was available for the student
teachers to add written comments about their perceptions of their teaching ability. When
completed, the researcher checked the accuracy between the Q-sort and the response sheet.
Data from the 28 participants were analyzed using the software PQMethod (2.11) (Schmolck,
2002). The Q-sorts for each of the 28 student teachers was entered into PQMethod to develop a
correlation matrix. The 28 x 28 matrix correlated each individual sort to all other sorts to
determine the level of agreement or disagreement between all viewpoints. Next, a factor analysis
of the correlation matrix was performed using principal component analysis (PCA). The PCA
was used to calculate a factor matrix which established the number of natural groupings that
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occurred from the student teachers’ perceptions on their teaching ability. PCA also produced
eigenvalues (i.e., percentage of factor variance) as part of its calculations. The eigenvalues were
subjected to a scree test, which allowed for the visual identification of three factors. Three
factors were rotated with varimax to produce a final factor solution.
To establish a significance level at p < .01, a ±0.43 significance criterion was calculated using
the equation: 2.58 SE (1/ N ), where N = the number of Q statements (36 statements for this
study). All Q-sorts were examined and those with a factor loading of ±0.43 significance or
higher on only one factor were identified as defining a factor, i.e., a person whose views highly
agree with their respective factor loading. Twenty-one of 28 sorts loaded significantly on one of
three factors. Factor 1 had 12 defining Q-sorts, Factor 2 had five defining Q-sorts, and Factor 3
had four defining Q-sorts.
Seven Q-sorts were identified as non-significant or confounding and therefore were not used in
the interpretation of factors. Non-significant Q-sorts are those which did not meet the ±0.43
significance criterion; thus, three participants did not share a viewpoint which was captured in
the factors of this study. Confounding Q-sorts met the ±0.43 significance criterion for more than
one factor. Four participants’ viewpoints were not “pure,” that is, they shared multiple
viewpoints. Only pure, single load Q-sorts were used in this study.
Factor scores were calculated for each statement within each of the factors according to its
placement within that factor. The calculated factor scores are presented as z-scores. A z-score
measures how far a statement lies from the middle of a distribution (Shemmings, 2006). Using
the z-scores, a model Q-sort, or factor array, was generated for each factor. A factor array
“represents how a hypothetical respondent with a 100% loading on that factor would have
ordered all the statements of the Q-set” (van Exel & de Graaf, 2005, p. 9). Statements with the
highest z-scores are those with a factor array position of +4. Statements with the lowest z-scores
are those with a factor array position of -4.
Interpretation of the factors involved an examination of the factor array of statements created for
each factor. A factor array tells a story with the placement of the positively and negatively placed
statements. Statements of neutrality also may be an important element of the story depending on
what a researcher is seeking. The interpretation was constructed by a careful consideration of
“most like” and “most unlike” statements both individually and holistically. As the viewpoints
began to evolve, consideration was then given to distinguishing statements and consensus
statements. The final refinement of the viewpoint came with an examination of the qualitative
comments gathered from the student teachers’ written comments on the Q-sort form.
Distinguishing statements are those that had a statically distinct placement in a factor array in
comparison to its placement in other factors arrays. Such statements help define the unique
viewpoints of a factor. As such, the z-score of a distinguishing statement may or may not be
imperative to the researcher due to the context of the interpretation, i.e., a low z-score may still
produce a statically distinct statement. Z-scores are important for intra-factor interpretations,
whereas distinguishing statements are important for inter-factor interpretations. Distinguishing
statements for this study were those which met the significance level p < .05. Earlier, p < .01
significance was used to establish the ±.043 criterion for identifying defining Q-sorts, i.e.,
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April 20-23, 2011
identifying people who highly agreed with the views represented by their respective factor;
whereas, p < .05 was used for identifying distinguishing statements, i.e., the placement of
statements that were ranked significantly different between the differing views. Using a less
stringent significance value for distinguishing statements helped to optimize the number of
statements that differed between each factor, which led to ease of interpretation (van Exel, 2005).
Factor 1: Emerging Teacher
This factor was defined by 12 of the Q-sorts and accounted for 22% of the variance in the
analysis. This view did not feel that teaching was particularly easy (statement 2, z-score -1.23)
(Table 1). Yet, these individuals recognized that they were getting better at teaching (4, 1.56) and
perceived to need less help teaching than they did before (7, 1.02). In addition, they liked how
teaching made them feel overall (1, 1.36). Written comments which supported this point of view
were “They [my classes] are all good and going great” (participant 6) and “[I] hope that the rest
of my experience is as enjoyable” (participant 3). These student teachers recognized they were
still growing as a professional (28, 1.72). This continued growth aspect was emphasized further
with the “most unlike me” placement of two distinguishing statements; “I have enough training
to deal with student learning problems” (15, -1.24), and “I know how to individualize
instruction” (18, -0.86). Participant 22 said, “I feel that I would have liked to know a little more
about which IEP [Individualized Education Plan] students have.” IEPs are implemented in the
school system and are designed to meet the particular educational needs or learning problems of
a specific student. This participant’s comment can be related back to the growth needed as a
teacher in relation to the aforementioned statements concerning individualized instruction and
management of student learning problems. In addition, those with this view failed to understand
how children learn and develop (14, -0.79). Nor did these student teachers know how and where
to refer students with learning problems (16, -0.82). These statements defined the student
teachers’ awareness that he/she needed more growth in this area.
Table 1
Factor 1: The Emerging Teacher View: High and Low Ranking Statements
No.
“Most Like” Statements
29.* I feel comfortable with my ability to communicate with colleagues and
parents.
28. I have learned ways to grow as a professional.
20.* I know how to encourage positive social interactions.
4.
I am getting better at teaching.
1.
I like how teaching makes me feel.
21.* I am able to handle discipline problems in my classroom
19. I feel comfortable with my classroom management skills.
7.
I need less help with teaching than I did before.
5.* I am confident in my ability to teach.
24.* I feel comfortable with my ability to motivate students.
14.
26.
16.
“Most Unlike” Statements
I understand how children learn and develop.
I am able to use prescribed curriculum for instruction.
I know how and where to refer students with learning problems.
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Array
Position
4
Z
score
1.74
4
3
3
3
3
2
2
2
2
1.72
1.61
1.56
1.36
1.12
1.03
1.02
0.78
0.75
-2
-2
-2
-0.79
-0.82
-0.82
18.* I know how to individualize instruction.
-2
-0.86
32. I can construct lesson plans for only the subjects I am comfortable with.
-3
-1.18
2.* Teaching is easy for me.
-3
-1.23
15.* I have enough training to deal with student learning problems.
-3
-1.24
35.* I can teach any agricultural education course.
-3
-1.36
34. It is easy to find curriculum materials to instruct with.
-4
-1.43
33. I feel comfortable teaching only one or two subjects.
-4
-2.06
Note. The table displays the top ten “most like me” and “most unlike me” statements; *Denotes a
distinguishing statement; p < .05.
Student teachers holding the Emerging Teacher view clearly did not feel comfortable teaching
all aspects of agriculture, as defined by the rejection of the distinguishing statement, “I can teach
any agricultural education course” (35, -1.36) (Table 1). Participant 13 wrote, “I am learning in
ag[ricultural] mechanics and will continue to do so, but basic welding [is] what I am comfortable
with now.” Although these student teachers did not feel comfortable teaching all agricultural
education courses, they did feel strongly about their ability to teach several different agricultural
subjects due to their rejection of the statement, “I feel comfortable teaching only one or two
subjects” (33. -2.06). However, despite any discomfort in teaching across the curriculum, these
student teachers had no problem creating lesson plans across the curriculum. This aspect is
supported by their rejection of the statement, “I can construct lesson plans for only the subjects I
am comfortable with” (32, -1.18). Participant 12 explained, “I just have to do my part in
researching/studying the topics before I actually teach it to my students.”
The Emerging Teacher view can construct lessons across the curriculum, but finding the
materials to do so was no easy feat (34, -1.43). These student teachers felt unable to use
prescribed curriculum for instruction (26, -0.82); yet, when pursuing the creation of their own
materials, it was not easy to find curriculum materials with which to instruct (34, -1.43). Unique
to this view was a social dimension. Particularly noteworthy were three “most like me”
distinguishing statements. These were, “I feel comfortable with my ability to communicate with
colleagues and parents” (29, 1.74), “I know how to encourage positive social interactions” (20,
1.61), and “I feel comfortable with my ability to motivate students” (24, 0.75)). This social
dimension of those holding the Emerging Teacher view also trickled down to their comfort with
classroom management skills (19, 1.03). Their knowledge in encouraging positive social
interactions was emphasized by another distinguishing statement, “I am able to handle discipline
problems in my classroom” (21, 1.12).
Factor 2: Self-Assured Teacher
This factor was defined by five of the Q-sorts and accounted for 17% of the variance in the
analysis. The Self-Assured Teacher view was confident in their teaching ability (statement 5, zscore 2.19) and classroom management skills (19, 0.84) (Table 2).
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April 20-23, 2011
Table 2
Factor 2: The Self-Assured Teacher View: High and Low Ranking Statements
No.
5.
3.*
23.
2.*
1.
6.*
8.
12.
35.
19.
I am confident in my ability to teach.
When I teach, I feel satisfied.
I feel comfortable with my ability to plan instruction.
Teaching is easy for me.
I am relaxed when I teach.
My students think I teach well.
My lessons contain meaningful learning experiences.
I can teach any agricultural education course.
I feel comfortable with my classroom management skills
Array
Position
4
4
3
3
3
3
2
2
2
2
Z
score
2.19
1.58
1.37
1.26
1.15
1.06
0.91
0.88
0.85
0.84
34.* It is easy to find curriculum materials to instruct with.
-2
-0.54
15. I have enough training to deal with student learning problems.
-2
-0.69
14. I understand how children learn and develop.
-2
-0.70
30.* I have observed teaching that I will model in the future.
-2
-0.95
25. I have observed other teachers techniques to motivate students.
-3
-0.98
17. I have observed other teachers deal with student learning problems.
-3
-1.01
26. I am able to use prescribed curriculum for instruction.
-3
-1.20
36. I have observed other teachers use a variety of materials to build
-3
-1.22
lessons with.
32.* I can construct lesson plans for only the subjects I am comfortable with.
-4
-2.17
33. I feel comfortable teaching only one or two subjects.
-4
-2.25
In addition, these student teachers felt they could teach any agricultural education course (35,
0.85). This was emphasized further with the “most unlike me” placement of the distinguishing
statement, “I feel comfortable teaching only one or two subjects” (33, -2.25,). Participant 17
supported the view of being able to teach any agricultural education course by writing, “I really
feel that I was prepared for [the] content.”
The high confidence of the Self-Assured Teacher was emphasized with other statements as well.
The “most like me” placement of two distinguishing statements, “Teaching is easy for me” (2,
1.26), and “I am relaxed when I teach” (6, 1.06) added to the interpretation of comfort and
confidence (Table 2). Although, this view was comfortable and confident in their own teaching
ability, they had not observed teaching that they will model in the future (30, -0.95).
In terms of finding quality curriculum, the Self-Assured Teacher struggled. The distinguishing
statement, “It is easy to find curriculum materials to instruct with” (34, -0.54), was rejected
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April 20-23, 2011
(Table 2). And, while curriculum was difficult to find, these student teachers did not want to use
prescribed curriculum for instruction (26, -1.20) either. Participant 15 wrote, “Good curriculum
is the key, not having to go home at night and fill in gaps would be beneficial.” This supported a
view that these student teachers wanted quality instructional curriculum. It was noteworthy that
they have not observed other teachers use a variety of materials to build lessons with (36, -1.22).
The Self-Assured Teacher expressions of confidence regarding their ability to teach any
agricultural education course was also tied to their confidence in planning instruction. The
struggle in locating curriculum materials did not affect their ability in lesson planning. These
student teachers felt their lessons contained meaningful learning experiences (12, 0.88), and they
were comfortable with their ability to plan instruction overall (23, 1.37) (Table 2). They also
were confident in their ability to construct lessons across the agricultural education curriculum as
expressed by their rejection of the statement, “I can construct lesson plans for only the subjects I
am comfortable with” (32, -2.17). This is an interesting view, because through personal
comments, the student teachers did not seem to plan for many classes. Participant 7 claimed to
“use the same lesson plan for both horticultural classes,” and Participant 4 stated his classes were
“somewhat cover-all in subject matter…all ag[ricultural] subjects [were taught] inside one class
so the students get a broad view of ag[riculture].”
Although confident the Self-Assured Teacher view felt unprepared in some areas of teaching.
They do not feel they had enough training to deal with student learning problems (15, -0.69) nor
did they understand how children learn and develop (14, -0.70) (Table 2). These student teachers
have not observed other teachers model the teaching tasks specified. They rejected the
statements, “I have observed other teachers deal with student learning problems” (17, -1.01), and
“I have observed other teachers techniques to motivate students” (25, -0.98). Further, teaching
not only evoked confidence for the Self-Assured Teacher but feelings of pleasure and satisfaction
as well. A “most like me” statement included, “I like how teaching makes me feel “(1, 1.15), and
a distinguishing statement was, “When I teach, I feel satisfied” (3, 1.58).
Factor 3: Determined Teacher
This factor was defined by four of the Q-sorts and accounted for 12% of the variance in the
analysis. This group was named the Determined Teacher because of its balance of teaching
confidence and hard work. Participants with this view had confidence in their teaching ability yet
felt they were still growing as a teacher and professional (4, 1.68; 7, 0.73) (Table 3). This type of
student teacher felt strongly that teaching was not particularly easy (statement 2, z-score -1.92).
In addition to teaching not being easy, these student teachers had perceived feelings of stress and
tension in relation to teaching. Two “most unlike me” distinguishing statements verified this
view firmly: “I am relaxed when I teach” (6, -2.37), and “When I teach, lessons flow” (11, 1.08). Yet, countering the perceived feelings of teaching stress, the Determined Teacher view
recognized a level of confidence in their ability to teach (5, 2.02). They needed less help teaching
than before and were growing as a professional (28, 1.34). In addition, teaching was a source of
pleasure to this group (1, 1.37). The Determined Teachers’ confidence was supported by others’
thoughts on their teaching ability. This was expressed in the “most like me” statement, “My
students think I teach well” (8, 0.80).
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Table 3
Factor 3: The Determined Teacher View: High and Low Ranking Statements
No.
5.
4.
1.
28.
12.
30.*
35.
23.
8.
7.
I am confident in my ability to teach.
I am getting better at teaching.
I have learned ways to grow as a professional.
My lessons contain meaningful learning experiences.
I have observed teaching that I will model in the future.
I can teach any agricultural education course.
I feel comfortable with my ability to plan instruction.
My students think I teach well.
I need less help with teaching than I did before.
Array
Position
4
4
3
3
3
3
2
2
2
2
Z
score
2.02
1.68
1.37
1.34
1.09
1. 02
0.84
0.81
0.80
0.73
22. I have observed other teachers’ classroom management procedures.
-2
-0.67
24.* I feel comfortable with my ability to motivate students.
-2
-0.71
20. I know how to encourage positive social interactions.
-2
-0.75
17. I have observed other teachers deal with student learning problems.
-2
-0.87
32. I can construct lesson plans for only the subjects I am comfortable with.
-3
-0.89
11.* When I teach, lessons flow.
-3
-1.08
34. It is easy to find curriculum materials to instruct with.
-3
-1.26
36. I have observed other teachers use a variety of material to build lessons with. -3
-1.72
2.* Teaching is easy for me.
-4
-1.92
6.* I am relaxed when I teach.
-4
-2.37
Unique to the Determined Teacher, however, was the distinguishing statement, “I have observed
teaching that I will model in the future” (30, 1.02) (Table 3). This was interesting because of
their ranking of other statements, i.e., they had not seen teachers perform several important tasks
associated with teaching. They rejected three statements associated with the observation of other
teachers. Those three were, “I have observed other teachers’ classroom management procedures”
(22, -0.67), “I have observed other teachers deal with student learning problems” (17, -0.87), and
“I have observed other teachers use a variety of materials to build lessons with” (6, -1.72).
However, not seeing others teachers complete these tasks did not interfere with the Determined
Teachers’ views on completing these tasks for themselves. In terms of curriculum planning and
instruction, these student teachers expressed comfort with their ability to plan instruction (23,
0.81) and create lessons with meaningful learning experiences (12, 1.09).
In addition, these student teachers felt they could teach any agricultural education course (35,
0.84). They also perceived they could construct lesson plans for more than just the subjects with
which they were comfortable (32, -0.89). Participant 20 emphasized this by stating, “I feel
comfortable with [all] the agriculture subjects.” This participant did mention a lack of comfort
with the agricultural communications curriculum, however. And, although these student teachers
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April 20-23, 2011
perceived they could construct lesson plans, finding the actual materials needed for the
development of the curriculum was not easy for them. To that end, these student teachers
rejected the statement, “It is easy to find curriculum materials to instruct with” (34, -1.26).
Conclusion/Discussion
The three factors produced from the Q-method factor analysis represented the three distinct
views found in the sample population of agricultural education student teachers regarding their
perceptions of teaching ability during the clinical student teaching experience. The three views
were interpreted as the Emerging Teacher, the Self-Assured Teacher, and the Determined
Teacher. The Emerging Teacher view was interpreted as those student teachers who recognized
areas in which they still needed growth and development but also recognized their development
toward becoming a professional. Teaching was not easy for them, especially in instructing the
diverse curriculum areas found in agricultural education courses; yet, they felt confident in
planning lessons for all agricultural subject areas. They had a unique social dimension which
made them more comfortable when motivating students, communicating with colleagues and
parents, and dealing with teaching responsibilities such as classroom discipline and management.
The Self-Assured Teacher view was comfortable and confident in their teaching ability. This
confidence extended to their views on developing lessons and teaching across the agricultural
education curriculum. Despite not having observed model teaching, this view could create lesson
plans and manage a classroom effectively. The Self-Assured Teacher view also expressed that
teaching was easy, and, as such, they were satisfied with their abilities.
The Determined Teacher view consisted of those student teachers who exhibited confidence but
were not yet comfortable in their teaching ability. Teaching did not always come easy for them,
but they recognized that they were getting better. These student teachers were not relaxed when
they taught, their lessons did not flow, and they had difficulty locating appropriate curricular
materials. However, these student teachers were confident in their ability to construct lesson
plans and provide instruction across the agricultural education curriculum. These student
teachers had observed teaching that they would prefer to model. The Determined Teacher view
consisted of those who were persistent in their efforts in becoming a “quality” teacher.
Across all three views, only the Determined Teacher viewpoint observed quality teaching being
modeled. This is unfortunate because observation of effective models improves a person’s
efficacy at performing similar tasks (Bandura, 1997), especially in regard to teaching
(Tschannen-Moran et al., 1998). Further, when considering social persuasion, it is easier to gain
and maintain a sense of efficacy when significant others profess faith in a person’s abilities
(Bandura, 1997). For a student teacher, this “significant other” may be a cooperating teacher,
university supervisor, or the pupils being instructed. However, across all three views, the student
teachers indicated neutrality on the statements, “My cooperating teacher thinks I teach well,” and
“My university supervisor thinks I teach well.”
The Determined Teacher view admitted discomfort in teaching by rejecting the statements that
teaching was easy and relaxing for them. Tschannen-Moran et al. (1998) explained that moderate
levels of emotional arousal may improve performance by focusing attention and energy on the
11
April 20-23, 2011
task at hand. Student teachers with this view may have experienced the correct amount of a
heightened emotional state to help them strive for success in the teaching tasks they attempted.
Implications
Student teaching is a valuable aspect of any teacher education program (Schumann, 1969).
Teaching efficacy can affect a student teacher’s performance while interning (Tschannen-Moran
et al., 1998). Therefore, implications exist for the placement of student teachers as well as the
amounts and types of feedback provided to them. Why were some students more assured of their
ability than others? Could a different set of experiences at the pre-service level help student
teachers perceive themselves as being more efficacious regarding their teaching performance?
Other than the 36 statements used to capture these participants’ views, what other factors
contributed to their perceptions?
Can the three views which emerged in this study be linked back to the cognitive learning style of
the student teacher? According to Witkin, Moore, Goodenough, and Cox (1977), students with a
field-dependent learning style are those who are global consumers of information, have difficulty
breaking down tasks into parts, have highly developed social skills, are socially influenced, and
extrinsically motivated. The Emerging Teacher view held a distinct social dimension that did not
appear in the views. Witkin et al. (1977) explained that students with a field-independent
learning style are those who are more analytical, goal-oriented, self-directed, intrinsically
motivated, and can view tasks as discrete parts. The Self-Assured Teacher view was confident
and comfortable with their teaching ability. As such, could their confidence be linked to the
field-independent learning style? Like those who are oriented toward field-independence, the
student teachers of the Determined Teacher view appeared to be motivated intrinsically because
they were determined to work through the discomforts of teaching. However, their discomforts
in their teaching ability may be derived from an inability to break down teaching tasks into
smaller chunks, like those who are orientated toward field-dependence.
Recommendations
This study should be replicated with a different population of student teachers to determine if the
same teaching ability views emerge. Also, future research should be expanded to gather data
over time. Specifically, a longitudinal study during the entire student teaching internship could
offer information on how student teachers differ at various stages of their internship experience.
It would be helpful to collect data on the same group of student teachers prior to, during, and
after they have finished their student teaching experience at the cooperating center. Collecting
data at these intervals would allow a researcher to determine the impact of the student teaching
experience on teachers’ views of efficacy, as well as offer multiple views on assisting student
teachers to improve on their deficiencies during their student teaching internship. Further,
following a specific population of student teachers over time might lead to insights on how their
self-efficacy regarding teaching ability may change as they transition into the first year of
teaching and beyond. Does teacher self-efficacy increase (Hoy & Woolfolk, 1990) or decrease
(Knobloch & Whittington, 2003) after student teaching?
This study examined the perceptions of student teachers on their abilities and competencies as
teachers holistically. The condition of instruction could be rewritten as, “How do you feel about
each course you instruct?”. This study should also be replicated to include the views of interns’
12
April 20-23, 2011
cooperating teachers as a form of triangulation. Also, follow-up interviews have shown to be
helpful in the interpretation of the statements for each factor when using Q-methodology.
Therefore, an increase in the number and depth of follow-up interviews should be conducted.
Roberts and Dyer (2004) noted that being a secondary agricultural education teacher includes
more than classroom teaching. As such, Q-statements should be refined to capture other teaching
activities unique to agricultural education. In particular, Q-statements should be developed to
include the remaining aspects of a comprehensive agricultural education program, i.e., SAE and
FFA. Information from such a study could provide insight into student teachers’ views on those
activities with regard to mastery experiences (Bandura, 1986, 1997).
13
April 20-23, 2011
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Identifying Specific Items for Non-Traditional Education Programs
Caleb D. Dodd, Scott Burris, Ph.D., Steve Fraze, Ph.D., David Doerfert, Ph.D, Abigail
McCulloch, M.S.
The incorporation of hot and cold food bars into grocery stores in an effort to capture a
portion of the home meal replacement industry is presenting new challenges for retail food
establishments. To ensure retail success and customer safety, employees need to be educated in
food safety practices. Traditional methods of training are not meeting the needs of the retail
food industry. Although many food safety training programs exist, few meet the educational
needs of hot and cold food bar employees. In an effort to identify specific items that are not
being addressed in current food safety training programs for employees a quasi-experimental
study was performed. Data was collected from three separate chains within the retail food
industry from six geographical locations. The pre-post assessment study utilized an
interventional training and included collecting questionnaires from 139 employees. Findings of
the study identified specific items that are not effectively being covered in the hot and cold food
bar industry creating a food safety concern. Food safety knowledge of employees within the hot
and cold food bar sector was assessed. The most important finding for this study was identifying
critical items and important items for food safety training curriculum.
Introduction-Theoretical Framework
While food supply in the United States is one of the safest in the world, the Centers for
Disease Control and Prevention estimates 76 million cases of foodborne illness occur each year,
more than 325,000 individuals are hospitalized, and 5,000 die from foodborne illness (Foodborne
Illness, 2010). In addition to the threats of foodborne outbreaks on health, financial implications
to the industry are also apparent. The complex food system in the United States, high employee
turnover, and strengthening pathogens, have lead to an increasing need for food safety
curriculum in the grocery store industry (Binkley & Ghiselli, 2005).
An organized approach is necessary to identify and fulfill training needs. In 2006,
organizations spent $129.6 billion dollars on training to prepare employees for conducting their
tasks (Moskowitz, 2008). With such a sizable investment, organizations must prioritize and
focus training resources where they will be most effective. One way of providing this focus is
through the utilization of a needs assessment. A needs assessment is the process of identifying
needs, prioritizing them, making needs-based decisions, allocating resources, and implementing
actions in organizations to resolve problems underlying important needs (Altschuld & Kumar,
2010). Moskowitz (2008) found that the most efficient way to collect data for a training needs
assessment is through surveys and assessments to tests employees’ job knowledge.
There are many methods for conducting a needs assessment. In 1984, Witkin developed
a process model that contained three phases and emphasized three levels of need (Altschuld &
Kumar, 2010). Since then, Altschuld and Kumar (2010) have revised the model.
Phase I of the needs assessment model consists of becoming organized and focusing on
potential areas of concern. This includes exploring literature and research to determine what is
April 20-23, 2011
already available and its level of success as it relates to the specified focus of each employer.
Phase I is a critical building block of a needs assessment as it leads to a wealth of information
about the areas of concern. The purpose of this phase is to take advantage of existing data
(Altschuld & Kumar, 2010). Previously literature of curriculum development and identifying
training needs within the grocery industry was researched to complete Phase I of the needs
assessment.
Phase II deals with gathering new information based on what has not been discovered in
Phase I. Phase II involves determining initial needs, prioritizing these needs, and analyzing their
possible solution strategies. Phase II often requires an extensive investment of time, personnel,
and resources for the collection of new data (Altschuld & Kumar, 2010). A pre-test/post-test
study was conducted to establish a wealth of new data for Phase II of the needs assessment.
Designing and implementing solutions for high-priority needs and evaluating the results
of the needs assessment process constitute Phase III. Evaluation of the process generally is not
done but should be completed as part of organizational development and change (Altschuld &
Kumar, 2010). Specific items were identified and recommended for the development of
curriculum for the target population to complete Phase III of the needs assessment.
In order to train employees in proper food safety, it is vital that high standards are set in
the development of the curriculum used to create the training programs that are both productive
and effective. There are many recommendations when it comes to developing curriculum for the
food safety industry. Litwak (1998) identified three avenues of food safety: preparation, storage,
and handling. Lawn (2008) recommended the use of creative and fresh ways to communicate the
importance of food handling practices. Using many different examples and scenarios helps to
make the training more realistic and applicable (Lawn, 2008).
There have been a variety of different training programs developed for food safety in
order to educate employees involved in the food service industry. Instructional materials must
be both instructionally effective and cost effective (Lawn, 2008). Sinclair et al. (2003) found
curriculum was developed for needs identified by focus groups. The results from these groups
revealed food service employees wanted simple-to-use and easy-to-understand materials that
could be used in a variety of situations. The focus groups also requested that material be colorful
and dominated by pictures and illustrations (Sinclair et al., 2003).
There is a lot to consider when designing a new curriculum. Lawn (2008) found a
technique referred to as spot-the-error to be very effective when developing curriculum. Green’s
(2008) research showed the need for food safety interventions that do more than provide food
safety curriculum. Biech (2009) suggested that perhaps the most important part of developing
curriculum is ensuring that the curriculum is engaging and interesting to the desired audience.
Moskowitz (2008) stated that it is important to know the goals of the training program and how
the success will be measured, the key topics that will need to be covered and in what sequence,
what training medium will be used, and some background knowledge of the organization’s
environment and culture.
In addition to training strategies, many food safety certifications have been developed to
meet the national and state requirements for health inspections. The majority of these
April 20-23, 2011
certifications are focused on employees working in the dine-in sector of the industry (Green &
Selman, 2005). The national Restaurant Association Educational Foundation sponsors the
country’s most prominent food safety training program in ServSafe® (Hertzman & Barrash,
2007). ServSafe® delivers high-quality training programs from classroom to online in a variety
of languages (ServSafe® Training and Certification, 2010). Since its introduction in 2004
SuperSafeMark® has quickly grown in popularity as a preferred method of food safety training
for managerial employees, associates, and professional trainers. SuperSafeMark® is a
comprehensive food safety training and certification program for the retail and wholesale food
industry (Food Marketing Institute, 2010).
The purpose of this study was to identify specific items to focus on when developing a
food safety training curriculum for non-traditional education programs for employees in the hot
and cold self-service food bars of grocery stores. Findings from this study will be used to
determine what information should be included into an educational curriculum and the most
effective way of presenting the curriculum using computer-based instruction. The needs
assessment utilized a pre-test/post-test design to determine educational needs of employees
beyond basic food safety training that is already being provided in the industry.
This study is directly related to the third (Identify appropriate learning systems to be used
in non-formal education settings), fourth (Examine appropriate non-formal educational delivery
systems), and fifth (Identify and use evaluation systems to assess program impact) research
priority areas of Agricultural Education in Domestic and International Settings: Extension and
Outreach of the National Research Agenda for Agricultural Education and Communication. In
order to successfully complete this study, a process was determined to identify food safety items
that were not positively affected by either an interventional food safety training or time in the
industry. The needs assessment was guided by one primary objective:
1. Identify specific items to be addressed in the development of food safety training
curriculum.
The research design for this study was quasi-experimental. This type of experiment lacks
random assignment but can yield useful knowledge if it is carefully designed (Gall, Gall, &
Borg, 2007). The study contained an education intervention. Initial assessment of essential food
safety knowledge was pre-test, followed by an interventional food safety training program for
managerial employees, and followed by a post-test assessment.
With the intention of developing a computer-based training program for hot and cold
self-service food bars in the grocery store industry the United States Department of Agriculture
(USDA) funded a research grant through the International Center for Food Industry Excellence
(ICFIE). Three grocery chain retail food providers agreed to participate in the collaborative
project. The chains span six geographical regions within five states. In order to properly assess
the effectiveness of food safety training it was determined that both managerial and nonmanagerial employees should be included in the study. The target population included
April 20-23, 2011
employees that worked in the hot and cold self-serve food bar department of grocery stores. The
sampling technique used for this study was non-probabilistic purposive.
The grocery chains agreed to allow one managerial employee and two non-managerial
employees complete a written questionnaire. Following the initial data collection period,
managerial employees participated in an interventional food safety training program. The
interventional food safety training the managerial employees received was presented by
professionals using certification curriculum. Post-training data was collected no less than 30
days later, this period of time gave managerial employees time to transfer new knowledge to
non-managerial employees within the stores. Post-training data included the same questionnaire,
again targeting one managerial employee and two non-managerial employees. After the
collection of the data, analysis was performed to identify items that were not being effectively
addressed in food safety training currently available in the industry.
The accessible sample for the needs assessment consisted of 20 stores from three grocery
chains in five states who offered hot and cold self-service food bars for customers. The 20 stores
were represented by 139 questionnaires. Twenty-seven managerial employees and 56 nonmanagerial employees participated in the pre-assessment of food safety knowledge, whereas 16
managerial employees and 40 non-managerial employees participated in the post-training
questionnaire. The sampling technique was non-probabilistic. Results of this study cannot be
generalized to a larger population due to the fact that the sample was purposively selected by the
chains upper management. However, the sampling technique does allow for adequate needs
assessment to be performed.
The instrument used for this study was a Food Safety Questionnaire developed for a preassessment to develop a food safety training program (McCulloch, 2009). The questionnaire
consisted of five sections. The questionnaire was developed in both English and Spanish. As
reported by McCulloch, the content and validity of the instrument used for this study was
established by a panel of experts. McCulloch reported the Kuder-Richardson 20 coefficient was
0.51. This is relatively low, but acceptable value for the Kuder-Richardson (Nunnally, 1967).
Two different modes were used for collecting data from employees. An online
instrument was initially developed for the delivery of the questionnaire; a paper booklet was then
designed to accommodate individuals without access to internet connections. The collection of
pre-test and post-test data spanned 15 months. The study was designed to offset data collection
between chains to reduce the number of personnel used data collection. Data from each chain
was collected within a 200-day period.
In analyzing data to address the objective, 16 questions from section two of the
questionnaire were used to determine food safety knowledge scores. The number of employees
who answered each question correctly was scored as a percentage of the total employees who
attempted to answer the question for participants in the particular group. An individual score
was calculated for both managerial and non-managerial employees for pre-assessment and postassessment for each question individually. Objective four identified specific items with the
greatest need for training that developed between the pre-training knowledge scores and posttraining knowledge scores using a quadrant analysis. This analysis of data was used to make
April 20-23, 2011
recommendations for the development of a computer-based training program and prioritize the
needs to be addressed.
The two groups consisted of the managerial employees and non-managerial employees.
A table was provided to record the groups’ specific scores on specific questions with the
frequency and percentage of correct responses. In order to adequately visualize the scores
reported in the tables, the percentage of correct responses for each question was plotted on
graphs. Pre-training scores for each question were plotted on the Y-axis going vertically and
post-training scores were plotted on the X-axis horizontally. Each of the 16 questions were
plotted and labeled using separate charts to represent each of the groups. A line was placed on
the median for both scores to provide four quadrants to assist in identifying needs for training
curriculum development.
Questions plotted in Quadrant #1 represent items that scored high on pre-training
assessment but low on post-training assessment. Questions that are plotted in this quadrant
represented topics that the time and/or treatment resulted in a negative effect. These items are
important when identifying topics to be addressed in curriculum development.
Questions plotted in Quadrant #2 represent items that scored high on pre-training
assessment and high on post-training assessment. Questions that are plotted in this quadrant
represented topics that time and/or treatment had little or no effect on due to the knowledge
already being existent. These topics are of the least importance when identifying areas of focus
for curriculum development.
Questions plotted in Quadrant #3 represent items that scored low on the pre-training
assessment and high on the post-training assessment. Questions plotted in this quadrant
represent topics on which time and/or training resulted in a positive effect. These items are not
of great importance in developing curriculum as knowledge scores in this quadrant are being
affected with current training and time.
Questions plotted in Quadrant #4 represent items that scored low on the pre-training
assessment and low on the post-training assessment. Questions plotted in this quadrant
represented topics on which time and/or training had little or no effect. This quadrant is the most
important quadrant for this study. Topics identified in this category are critical areas to address
for developing curriculum.
When describing the findings, the quadrants are addressed in level of importance
beginning with Quadrant #4, then discussing Quadrant #1, and finishing with Quadrant #2 and
Quadrant #3.
Findings
The frequency and percentages of accurate responses for each question answered
correctly by managerial employees for both the pre-training assessment and the post-training
assessment of the food safety knowledge portion of the questionnaire were reported in Table 1.
There were 27 managerial employees who participated in the pre-training questionnaire and 16
managerial employees who participated in the post-training questionnaire.
April 20-23, 2011
Table 1
Frequency of Correct Responses for Managerial Employees
Question
Pre-Traininga Post-Trainingb
f
%
f
%
Temperature Control
I-A. Foods that require proper temperature control to assure food safety
are referred to as – time/temperature control for safety foods
10
37.0
4
25.0
I-B. Time/temperature control for safety foods should not be
in the temperature danger zone more than – four hours
17
63.0
13
81.2
I-C. Maximum temperature for most refrigerated foods - 41ºF
23
85.2
16
100.0
I-D. Foods that are hot held should be at or above - 135ºF (57ºC)
12
44.4
8
50.0
II-A. Foodborne illness outbreak occurs – when 2 or more people
experience a similar illness after ingesting a common food
23
85.2
16
100.0
II-B. Bacteria grows best within the narrow range of temperatures
known as temperature danger zone - 41ºF (5ºC) - 135ºF (57ºC)
26
96.3
15
93.8
II-C. Most effective way to control the growth of bacteria in a retail
food establishment is by controlling – time and temperature
26
96.3
16
100.0
II-D. According to HACCP principles, what are critical limits – max and
min values that must be controlled to minimize risk of food safety hazard
22
81.5
14
87.5
III-A. Good personal hygiene includes – keeping
hands and clothes clean and sanitary
25
92.6
16
100.0
III-B. Four steps to effective cleaning and sanitizing – wash,
rinse, sanitize, and air dry
21
77.8
16
100.0
III-C. General rule for cleaning frequency of food contact
surfaces – anytime after contamination may have occurred
21
77.8
15
93.8
III-D. Number one contributing factor to foodborne illness
in retail establishments – cross contamination
10
37.0
2
12.5
IV-A. According to FDA Food Code, how often must temperatures
be taken for items on self-service food bars – every four hours
12
44.4
8
50.0
IV-B. Focus for food safety management programs – control time and
temperature, practice good hygiene, preventing cross contamination
23
85.2
13
81.2
IV-C. Which storage practice should prompt management to take
corrective action – raw poultry stores above potato salad
26
96.3
15
93.8
IV-D. When using utensils at a self-service food bar – use one utensil for
each food item, store utensil with the handle extending above rim
26
96.3
16
100.0
Foodborne Illness and Bacteria
Cleaning and Sanitation Practices
Management Policies
Note. an=27, bn=16
There were five questions (II-B, II-C, III-A, IV-C, and IV-D) that more that 90% of
managerial employees answered correctly in the pre-training assessment. There were no
April 20-23, 2011
questions on the pre-training assessment that managerial employees all answered correctly.
Questions I-A and III-D received the lowest frequencies in the pre-training with 37.0%
answering correctly. Other low frequency questions reported in the pre-training scores were
questions I-D (44.4%) and IV-A (44.4%), both having a frequency of 12.
There were six questions on the post-training assessment that 100.0% (n=16) of the
managerial employees answered correctly. These questions were I-C, II-A, II-C, III-A, III-B, and
IV-D. Other questions that that scored above 90% were questions II-B (93.8%), III-C (93.8%),
and IV-C (93.8%). The lowest score recorded in the post-training study was 12.5% for question
III-D. Other low frequency questions in the post-training assessment were questions I-A
(25.0%), I-D (50.0%), and III-D (50.0%).
The percentage of correct responses to the 16 questions answered in the pre-training and
post-training assessments of managerial employees were plotted in Figure 1. The median for
pre-training scores were 83.4%. The median for post-training scores were 93.8%.
120.0%
1
100.0%
II-B
Managerial
Employees'
Manager
Treatment
Scores Scores
80.0%
II-D
III-D
20.0%
Pre-Training
60.0%
40.0%
IV-C
IV-B
I-A
I-B
I-D
IV-D
2
III-A
II-C
II-A
I-C
III-B
III-C
IV-A
3 food safety
Figure 1. A4scatter graph
with percentage scores of correct responses to individual
Post-Training
0.0%
knowledge
questions plotted for the pre-training assessments and the post-training assessments
60.0%
80.0%
100.0%
120.0%
for the0.0%
managerial 20.0%
employees. 40.0%
Six questions (I-A, I-B, I-D, II-D, III-D, and IV-A) were plotted in Quadrant #4, the most
important quadrant for identifying specific topics to be addressed in curriculum development.
April 20-23, 2011
Three questions (II-B, IV-B, and IV-C) fell into Quadrant #1, also an important quadrant for
identifying areas to be addressed in curriculum development. Five questions (I-C, II-A, II-C, IIIA, and IV-D) fell securely in Quadrant #2, the least important quadrant for identifying specific
topics to be addressed in curriculum development. Two questions (III-B and III-A) fell into
Quadrant #3, also a less important quadrant for identifying areas to be addressed in curriculum
because the food safety knowledge is established over time in the industry.
The frequency and percentages of accurate responses for each question answered
correctly by non-managerial employees on both the pre-training assessment and the post-training
assessment for the food safety knowledge portion of the questionnaire were reported in Table 2.
There were 56 non-managerial employees who participated in the pre-training questionnaire and
40 non-managerial employees who participated in the post-training questionnaire.
There was one question answered correctly by more than 90% of the non-managerial
employees for the pre-training assessment. Fifty-three non-managerial employees (94.6%)
answered question IV-D correctly. There were five other questions with scores in the 80
percentile on the pre-training assessment. These questions were II-B (87.5%), II-C (83.9%), IIIC (83.9%), IV-B (89.3%), and IV-C (80.4%). Question I-D received the lowest frequency in the
pre-training with 12.5% of non-managerial employees answering correctly. There were four
other items that more than half of the non-managerial employees answered incorrectly on the
pre-training assessment. These included questions I-A (39.3%), I-B (44.6%), III-D (37.5%), and
IV-A (14.3%).
Seven questions in the non-managerial employees post-training assessment had more
than four out of five accurate responses. Questions with scores above 80% were questions II-C
(90.0%), II-D (80.0%), III-A (82.5%), III-C (92.5%), IV-B (82.5%), IV-C (85.0%), and IV-D
(95.0%). The lowest score recorded in the post-training study was 22.5% for question III-D.
Other low frequency questions with less than half of the non-managerial employees answering
correctly were I-A (25.0%), I-B (35.0%), I-D (25.0%), and IV-A (35.0%).
The percentage of correct responses to the 16 questions answered in the pre-training and
post-training assessments of non-managerial employees in the treatment group were plotted in
Figure 2. The median for pre-training scores were 70.6%. The median for post-training scores
were 76.3%.
There were seven questions (I-A, I-B, I-C, I-D, II-A, III-D, and IV-A) that were plotted
in Quadrant #4. Five of these seven were also plotted in Quadrant #4 for the managerial
employees. One question (II-B) fell into Quadrant #1. This question also fell into Quadrant #1
for the managerial employees. Seven questions (II-C, II-D, III-A, III-C, IV-B, IV-C, and IV-D)
fell securely in Quadrant #2. The last question (III-B) fell into Quadrant #3.
April 20-23, 2011
Table 2
Frequency of Correct Responses for Non-managerial Employees
Question
Pre-Traininga Post-Trainingb
f
%
f
%
Temperature Control
I-A. Foods that require proper temperature control to assure food safety
are referred to as – time/temperature control for safety foods
22
39.3
10
25.0
I-B. Time/temperature control for safety foods should not be
in the temperature danger zone more than – four hours
25
44.6
14
35.0
I-C. Maximum temperature for most refrigerated foods - 41ºF
37
66.1
30
75.0
7
12.5
10
25.0
II-A. Foodborne illness outbreak occurs – when 2 or more people
experience a similar illness after ingesting a common food
28
50.0
27
67.5
II-B. Bacteria grows best within the narrow range of temperatures
known as temperature danger zone - 41ºF (5ºC) - 135ºF (57ºC)
49
87.5
23
57.5
II-C. Most effective way to control the growth of bacteria in a retail
food establishment is by controlling – time and temperature
47
83.9
36
90.0
II-D. According to HACCP principles, what are critical limits – max and
min values that must be controlled to minimize risk of food safety hazard
42
75.0
32
80.0
III-A. Good personal hygiene includes – keeping
hands and clothes clean and sanitary
41
73.2
33
82.5
III-B. Four steps to effective cleaning and sanitizing – wash,
rinse, sanitize, and air dry
38
67.9
31
77.5
III-C. General rule for cleaning frequency of food contact
surfaces – anytime after contamination may have occurred
47
83.9
37
92.5
III-D. Number one contributing factor to foodborne illness
in retail establishments – cross contamination
21
37.5
9
22.5
8
14.3
14
35.0
IV-B. Focus for food safety management programs – control time and
temperature, practice good hygiene, preventing cross contamination
50
89.3
33
82.5
IV-C. Which storage practice should prompt management to take
corrective action – raw poultry stores above potato salad
45
80.4
34
85.0
IV-D. When using utensils at a self-service food bar – use one utensil for
each food item, store utensil with the handle extending above rim
53
94.6
38
95.0
I-D. Foods that are hot held should be at or above - 135ºF (57ºC)
Foodborne Illness and Bacteria
Cleaning and Sanitation Practices
Management Policies
IV-A. According to FDA Food Code, how often must temperatures
be taken for items on self-service food bars – every four hours
Note. an=56, bn=40
April 20-23, 2011
120.0%
1
2
IV-D
IV-C
IV-B
100.0%
III-C
III-A
Non-managerial
Scores
Employee
TreatmentEmployees'
Scores
80.0%
II-B
I-C
60.0%
20.0%
Pre-Training
I-A
I-D
40.0%
II-C
II-D
0.0%
0.0%
I-B
III-B
II-A
III-D
IV-A
4
3
Post-Training
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
Figure 2. A scatter graph with percentage scores of correct responses to individual food safety
knowledge questions plotted for the pre-training assessments and the post-training assessments
for the non-managerial employees.
There were five questions (I-A, I-B, I-D, III-D, and IV-D) that were plotted in Quadrant
#4 for both managerial and non-managerial employees. These five questions identify specific
topics that should be addressed in developing food safety curriculum. Question II-B appeared in
Quadrant #1 both times.
In summarizing the results it is important to understand that each question received one
score for managerial employees and a second score non-managerial employees, therefore, for
each of the four categories of questions there were eight questions plotted on the two graphs.
Seven of the eight questions related to Temperature Control were plotted in Quadrant #4 with
the last question being plotted in Quadrant #1. Two questions regarding Foodborne Illness and
Bacteria were plotted in Quadrant #4 and two more in Quadrant #1. Cleaning and Sanitation
Practices had the smallest number of questions plotted in Quadrant #4 and Quadrant #1 with
only two of the eight questions. Management Policies’ questions were plotted in Quadrant #4
and Quadrant #1 four of the eight times.
April 20-23, 2011
Collectively, 13 of the 32 questions plotted on the two scatter graphs were plotted in
Quadrant #4, with four other questions being plotted in Quadrant #1. Together, 15 questions
were plotted in Quadrants #2 and #3. These quadrants are less important for identifying specific
topics to address in curriculum development.
Conclusions-Implications-Recommendations
It is important that the computer-based food safety training program be structured in a
way that flows, is simple, and is valued by participants. Previous food safety training methods
used are acceptable for identifying material, but based on previous studies were not meeting the
needs of the hot and cold food sectors of grocery stores (McCulloch, 2009) (Hertzman &
Barrash, 2007).
Percentages of correct responses for each of the 16 questions answered by managerial
and non-managerial employees in the pre-training assessments and post-training assessments
were closely examined and reported. Specific topics were identified to be addressed in the
development of a computer-based food safety training curriculum.
Six questions were identified as being low-performing questions on both the pre-training
and post-training assessments for stores scores. These questions (I-A, I-B, I-D, II-B, III-D, and
IV-A) were answered correctly by the fewest number of participants in the study for both pretraining and post-training. These six questions were identified as critical items. Critical items
included time/temperature control for food safety, temperature danger zone concepts, food
holding temperatures, frequency of temperature measurements, cross contamination issues, and
bacteria growth temperatures. These six questions represent critical items to be included and
focused on in developing a computer-based food safety curriculum.
Five other questions were low-performing questions. These questions, I-C, II-A, II-D,
IV-B, and IV-C were answered correctly by a low percentage of participants for either
managerial or non-managerial employees. These five questions represent important items to be
addressed in developing food safety curriculum, but with less emphasis than items identified as
critical importance. Important items included refrigeration temperatures, foodborne illness
outbreaks, HACCP principles, food safety management programs, and proper storage practices.
Questions identified as critical items and important items are displayed in Figure 3. Questions in
the Temperature Control category were most frequently identified as critical items.
There were three questions plotted as high-performing questions (II-C, III-A, and IV-D)
for both groups. These questions were high performing on both the pre-assessment and again on
the post-assessment. These three questions are not important for topics for training curriculum
as they were a high knowledge prior to the training and remained a high knowledge area
following the training and time in the industry.
More than half the questions individually scored in this study represented topics that
should be addressed in future food safety training curriculum. Specific topics to be incorporated
into the modules for the food safety training with the highest level of importance should include:
time/temperature control, temperature danger zone, holding temperatures, proper procedures for
taking temperatures, and the causes of foodborne illnesses and outbreaks. Other specific topics
April 20-23, 2011
Important Items
Critical Items
I-C. Maximum temperature for most refrigerated
foods - 41ºF
I-A. Foods that require proper temperature
control to assure food safety –
time/temperature control for safety foods
II-A. Foodborne illness outbreak occurs – when
2 or more experience an illness after
ingesting a common food
I-B. Time/temperature control for safety foods
should not be in the temperature danger
zone more than – four hours
II-D. According to HAACP principles, what are
critical limits – max and min values that
must be controlled
I-D. Foods that are hot held should be at or
above - 135ºF (57ºC)
II-B. Bacteria grows best within the temperature
danger zone - 41ºF (5ºC) - 135ºF (57ºC)
III-D. Number one contributing factor to
foodborne illness in retail establishments –
cross contamination
IV-B. Focus for food safety management
programs – control time, temperature, cross
contamination
IV-C. Which practice should require
management action – raw poultry stored
above potato salad
IV-A. According to FDA Food Code, how often
must temperatures be taken – every four
hours
Figure 3. A summary of critical and important items plotted in Quadrant #4 and Quadrant
#1 for managerial and non-managerial employees in hot and cold self-service food bars for
the pre-training assessments and the post-training assessments.
that should be focused on in the food safety training curriculum include: cleaning and sanitation
procedures, food safety management policies, critical limits, personal hygiene, and
understanding store policies.
Researchers recommend that the computer-based food safety training curriculum be
developed utilizing recommendations and guidelines from Biech (2009), Moskowitz (2008), and
Macaulay and Pantazi (2006). Curriculum should be short and to-the-point while covering the
essential information to sufficiently train participants in food safety knowledge and skills
necessary to ensure food safety for hot and cold food sectors of grocery stores. The curriculum
should be fast paced and include multi-media visuals, audio, and opportunities to enhance
interaction. Only information that is pertinent to providing safe food for the consumers should
be included in the computer-based food safety training curriculum.
Further research should be conducted to identify if food safety knowledge align with food
safety practices within the industry. Observations and audits should be conducted to observe
behaviors employees within the hot and cold food bar industry and compare food safety
knowledge scores to food safety performance scores to more fully identify items for curriculum
development.
April 20-23, 2011
References
Altschuld, J. W., & Kumar, D. D. (2010). Needs Assessment: An Overview. Thousand Oaks, CA:
SAGE Publications.
Biech, E. (2009). 10 Steps to Successful Training. Danvers, MA, USA: American Society for
Training & Development Press.
Binkley, M., & Ghiselli, R. (2005). Food safety issues and training methods for ready-to-eat
foods in the grocery industry. Journal of Environmental Health, 68 (3), 27-31.
Food Marketing Institute. (2010). Retrieved April 2, 2010, from SuperSafeMark: Manager level
training.: http://www.fmi.org/supersafemark/?fuseaction=ssm_training
Foodborne Illness. (2010). Retrieved April 7, 2010, from Centers for Disease Control and
Prevention:
http://www.cdc.gov/ncidod/dbmd/diseaseinfo/foodborneinfections_g.htm#howmanycases
Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational Research, An Introduction (8th
Edition). Boston, MA: Pearson Education, Inc.
Green, L. (2008). Behaviorial science and food safety. Journal of Environmental Health, 71 (2),
47-49.
Green, L. R., & Selman, C. (2005). Factors impacting food workers' and managers' safe food
preparation practices: A qualitative study. Food Protection Trends, 25 (12), 981-990.
Hertzman, J., & Barrash, D. (2007). An assessment of food safety knowledge and practices of
catering employees. British Food Journal, 109 (7), 562-576.
Lawn, J. (2008, March). To give training more impact, work on retention. Restaurant
Hospitality, 92 (5), pp. 112-114.
Litwak, D. (1998, September). Safety's seal of approval. Supermarket Business, 53 (9), p. 216.
Macaulay, M., & Pantazi, I. (2006). Material difficulty and the effectiveness of multimedia in
learning. International Journal of Instructional Media, 33 (2), 187-195.
McCulloch, A. (2009). A preassessment for developing a food safety training program for self
service food bars in grocery stores (Unpublished masters thesis). Texas Tech University,
Lubbock, TX.
Moskowitz, M. (2008). A Practical Guide to Training and Development. San Francisco, CA:
Pfeiffer.
April 20-23, 2011
Nunnally, J. C. (1967). Psychometric theory. New York: McGraw-Hill Book Company, Inc.
ServSafe Training and Certification. (2010, January). Retrieved March 10, 2010, from ServSafe:
http://www.servsafe.com/FoodSafety/
Sinclair, R. C., Smith, R., Colligan, M., Prince, M., Nguyen, T., & Stayner, L. (2003). Evaluation
of a safety training program in three food service companies. Jouranl of Safety Research,
34, 547-558.
April 20-23, 2011
Is Our Recipe Working? A Study of Current Teachers’ Perceptions on the Needed
Ingredients for Adequate Teacher Preparation
Abigail C. McCulloch, Scott Burris
Abstract
There is a need for agriculture, food, and natural resources teachers to be adequately
prepared for their future careers. Determining the needs of current teachers is an important task
in creating better university agricultural science teacher preparation programs. Preparing fully
qualified and highly motivated agricultural educators is one of the goals of the National
Research Agenda for Agricultural Education and Communications (Osborne, n.d.). In a survey
of agricultural science teachers there were 20 topics that the majority of teachers perceived as
very important for inclusion in university agricultural education programs. Over 70% of
teachers identified FFA, classroom management, leadership, and general animal science as
highly important topic areas. When asked what practice best prepared current teachers in each
content level, the most common responses were teaching experience and teacher preparation
education. Programs should be evaluated to ensure that they continue to provide the best
possible education in those areas for which current teachers identified teacher preparation
education as the best preparation practice. University level educators should examine the areas
where teaching experience best prepared current teachers to determine if instruction in those
areas could be improved to adequately address those areas during teacher preparation
programs.
Educators in any field face many obstacles and struggles within their careers. “The
beginning years of teaching can be very challenging” (Knobloch & Whittington, 2002b, p. 331).
According to the U.S. Department of Education (1997) during the first three years of teaching in
a public school 17% of teachers leave the profession. Teacher attrition is a critical issue in the
field of agricultural education and is costly to schools, students, communities, and the teachers
themselves (Crutchfield, 2010). The effectiveness of teachers is directly related to teacher
motivation and confidence (Miller, Kahler, & Rhealt, 1989).
Darling-Hammond (1997) completed a study in which teachers were identified as the
most important variable related to student achievement. This finding is supported by a study
conducted by Anderson in 1977, in which the success of an agricultural education program is
influence by teachers‟ beliefs and expertise. It is important that teachers are prepared to continue
to exert this influence through their beliefs and expertise.
Teachers need to be confident and efficacious in their teaching. In fact novice teachers
with a higher sense of efficacy are more likely to continue within our profession (Knobloch &
Whittington, 2002b). The National Commission on Teaching and America‟s Future (1996)
reported an attrition rate of 75% throughout the first three years of a teacher‟s career. Feelings of
loneliness, isolation, frustration, and stress were expressed by novice agriculture teachers in a
April 20-23, 2011
study conducted by Mundt (1991). These teachers also reported that they lacked needed
confidence. Teacher preparation is aimed at increasing confidence levels for teachers entering
the field. This will in turn help improve the feelings of those teachers and lower attrition rates.
The conceptual framework for this study is based on the same conceptual framework
Knobloch & Whittington (2002b) used in their study on teacher efficacy. Agricultural educators
will be more motivated, effective in helping students learn, resilient in difficult situations, and
stay in the profession longer if they are confident and have a high efficacy (Knobloch &
Whittington, 2002b).
Knowledge and education, as well as teaching and student teaching experience were
found to be in the top three factors that influence efficacy of novice teachers (Knobloch &
Whittington, 2002a). These factors are provided to future educators through teacher preparation
programs. Government agencies and researchers take teacher preparation seriously. There are
several studies that have identified needs areas for teacher preparation programs. Curriculum
development, learning styles, technical areas, teaching methods, teaching techniques, and
academic integration methods were areas that Dobbins and Camp (2000) identified as essential
to teacher preparation education. Facilitating student learning in laboratories and classrooms,
leadership and personal growth, and student agricultural experiences were found to be important
for teachers to understand by Edwards and Briers (1999). They also stated that teachers
themselves need to be competent in areas concerning student services, program management,
personal roles and relationships, and planning. Joerger (2002) added classroom management and
technical agriculture to the list needs.
This issue of adequately preparing agricultural educators is not new, and in fact has been
a concern for over 20 years. A higher level of competency is needed in teachers (Committee on
Agricultural Education in Secondary Schools Board on Agriculture of the National Research
Council, 1988). “As students, teachers, schools, curricula, legislation, and times change,
providers of teacher education preparation must also re-evaluate the content they distribute to
pre-service and current agricultural teachers” (Duncan, Ricketts, Peake, & Uesseler, 2006, p. 24).
Duncan et al. (2006) recognized the challenge of adapting teacher preparation to adequately
provide teachers with the needed knowledge. “Improving university agricultural teacher
education curricula and statewide continuing education programs calls for assessing the needs of
current practitioners of the „agriculture teaching‟ craft” (Duncan et al., 2006, p. 24).
The recommendations made by previous researchers‟ identified the theoretical
framework for this study. Witkin and Altschuld (1995) have provided a model for needs
assessments. Needs assessments were created based on the grounds that people have needs that
are not adequately being met or addressed (Witkin & Altschuld, 1995). In this study, these needs
are associated with better preparing agricultural science teachers for long successful careers. This
study was a preassessment of needs including initial data collection, which is the first phase of a
needs assessment (Figure 1).
April 20-23, 2011
Figure 1. Three-phase plan for needs assessment (Witkin & Altschuld, 1995).
Exploration is another word Witkin and Altschuld (1995) use to describe the first phase
of the model, preassessment. In this phase a management plan for the needs assessment is
created. The general purpose of the assessment is defined. Major needs and issues are
identified, as well as existing information that can be used to address needs. Data to collect,
sources, methods, and potential uses of data are determined in this first phase. Preassessment
data collection was the primary purpose of this study. This study will be used to plan and collect
more in depth information from teachers in Phase 2 of the needs assessment. The sources of
valuable information were identified as current teachers and university educators. Potential uses
of this data are included as a purpose of this study to improve university agricultural science
teacher preparations programs. The outcome of this phase is primarily planning. Phase 2 and
Phase 3 should be planned, as well as an evaluation of the complete needs assessment (Witkin &
Altschuld, 1995).
Program decisions are made based on information and perceptions of values during a
needs assessment (Witkin & Altschuld, 1995). Needs assessments are not focused on
individuals; instead they focus on diagnostic information on programs. This information leads to
changes in the program that will benefit individuals with needs. The primary beneficiaries of the
needs assessment are the people who ultimately benefit from the programs or who are provided
for through the system (Witkin & Altschuld, 1995). For this study, students enrolled in
agricultural science programs are the primary audience. For needs that can be met through
education programs assessments are most often times performed on level two, which consists of
service providers. This is the case for the needs assessment conducted in this study as
agricultural science teachers provide an education for their students.
April 20-23, 2011
Agricultural, food, and natural resource teachers need to be adequately prepared. The list
of competencies to include in these programs continues to evolve as evidenced in the literature
cited above. Current teachers are the experts on what issues are most important in today‟s
climate that surrounds educators. The purpose of this study was to determine current agricultural
teacher‟s perceptions of important topics to be taught within teacher preparation education.
These perceptions will be used to determine which content areas should be the focus of
university teacher preparation programs. The teacher perceptions reported during this study help
to compose the first phase of Witkin and Altschuld‟s needs assessment model which is
preassessment data collection (1995). The following objectives were developed in order for this
study to fulfill its purpose.
1. Describe agricultural, food, and natural resource teachers.
2. Determine topic areas that are highly important to agricultural, food, and natural resource
teachers.
3. Identify the best preparation practice for topic area used by agricultural, food, and natural
resource teachers.
There are many topics included in teacher preparation instruction. In order to understand
which topics were perceived as most important to agricultural, food, and natural resources
teachers, these teachers in a southern state were surveyed. The target population for this study
was all agricultural, food, and natural resource teachers in this particular southern state. The
accessible population was those teachers who attended their area meeting at the professional
development conference in the summer. The researcher introduced the questionnaire and
administered the survey at each of the area meetings. The responding population was the 227
teachers that returned the completed questionnaire at the end of the area meeting. Some of the
questionnaires were incomplete, as teachers did not answer all of the items. Due to the fact that
this was a convenience sample the results of this study cannot be generalized to the entire
population; however, valuable insight into teacher preparation can be gained through this study.
This includes what courses should be taught, as well as information on what role teacher
preparation programs play in providing needed knowledge for teachers.
The instrument was created by the researcher through a process that began with a search
of the curriculum provided in the top 10 agricultural education programs in the country
according to a study completed by researchers at the Ohio State University (Birkenholz &
Simonsen, 2009). Course names and topics were compared, duplicates were eliminated, and a list
was compiled. The next step in the process was a brainstorming session in which a panel of
agricultural educators derived a list of content areas that they felt were essential to their teacher
preparation education. This panel was asked to not only to think about topics taught in their
teacher preparation programs, but also to consider topics they would have benefited from
learning about in their teacher preparation programs. The topics that arose in this brainstorming
session were written in a list, compared to the previous list derived from the review of
curriculum, and grouped into three categories. The categories are agricultural content topics,
April 20-23, 2011
agricultural education topics, and general education topics. The agricultural content section
contained 14 items, the agricultural content was composed of 19 items, and there were 18 items
in the general agricultural education section. There was also a section of the questionnaire which
contained demographic questions and questions about previous experience of agricultural science
teachers.
Teachers were asked to rate the importance of each topic area for inclusion in teacher
preparation programs. These responses were on a scale of one to three where 1 = not important, 2
= important, and 3 = highly important. Teachers were then asked to place a check mark in the
box corresponding to the experience that best prepared them for their career as an agricultural
science teacher in relation to each topic area. The experiences they could choose from included
teacher preparation education, teacher in-service, teaching experience, other professional
experience, personal experience, and attending the summer professional development conference
for agricultural science teachers. Demographic information was also obtained from respondents.
Once the questionnaire was developed; it was approved for face and content validity by a
panel of experts in agricultural education. This instrument is in the early stages of research as it
was created by the researcher and used for the first time for this study. Therefore, a post-hoc
reliability coefficient of 0.71 was found. This level of reliability is acceptable for early stages of
research according to Nunnally (1967).
After data collection was completed it was entered into SPSS 17.0 to be analyzed. Due to
the nature of this data being descriptive, frequencies, means, and standard deviations were
calculated. Several correlations were run without producing any noteworthy results.
Results
The responding population in this study must be described before their perceptions of
important topics or their needs are determined. The gender gap of respondents in this study held
true to expectations for agricultural, food, and natural resource teachers with 72.6% male (n =
159) and 27.4% female (n = 60). The average number of years of teaching experience reported
by teachers in this study was 12.0 (SD = 10.5).
The majority of teachers in this study were certified through an undergraduate program (n
= 140, 64.5%). Graduate school was another popular method of certification (n = 53, 24.4%).
Only 8.3% of teachers were certified through a post-baccalaureate program (n = 18) and 2.8%
were certified through their regional education center (n = 6). A high majority of the teachers had
completed a student teaching experience during their teacher preparation education (n = 198,
98.5%). Most of the teachers held a bachelor‟s degree (n = 135, 59.5%) while the rest of the
teachers held master‟s degrees (n = 84, 38.4%). A large majority of the respondents completed
their undergraduate degree in agricultural education (n = 177, 81.3%), 16.1% of them have a
bachelor‟s degree in another agricultural field (n = 35). The other 2.8% (n = 6) completed their
bachelor‟s degree in a field unrelated to agriculture.
The agricultural, food, and natural resource teachers that participated in this study were
asked to determine the importance of early field observation and student teaching experience. Of
April 20-23, 2011
the 219 teachers that responded to these questions only 33.2% of them thought early field
observation was very important (n = 73), 53.2% of them (n = 115) thought it was important, and
13.6% (n = 30) did not think it was important. When asked about student teaching experience
77.1% of teachers thought it was very important (n = 168), while 17.4% (n = 38) thought it was
important. Only 5.5% (n = 12) of teachers thought that student teaching was not important to
teacher preparation education.
There were 19 agricultural content, 18 general education topics, and 14 agricultural
education topics. Respondents were asked to categorize these topics based on importance. The
teachers could label the topics very important (3), important (2), or not important (1). Out of the
total 51 topics there were 21 topics that the majority of agricultural science teachers felt were
very important (See Table 1). FFA was the topic that was deemed very important by the highest
percentage of teachers (84.0%, n = 179). The last topic included in Table 1 is award applications
and the majority of teachers still felt that this topic was very important (50.2%, n = 107). The
topics that were all rated as highly important by current agricultural science teachers can be
ranked upon themselves according to mean. The highest-ranking topic that was considered to be
very important by a majority of teachers was FFA (M = 2.84, SD = 0.37), while the lowest
ranking topic was award applications (M = 2.48, SD = 0.55).
Table 1
Very Important Topics for Teacher Preparation
Topic
%
FFA
84.0
Classroom management
79.4
Leadership
76.1
General animal science
70.5
Time management
67.2
SAEP
65.7
Agricultural youth leadership
64.3
Parent relations
62.0
General agricultural education
61.1
Livestock production
58.3
Public relations
57.9
Record keeping
57.5
Program management
57.3
Technology in the classroom
55.8
Teaching methods
55.3
Methods of teaching agriculture
54.4
Program structure
53.3
Agricultural careers
53.1
Interviewing and resume building
52.8
Organizational leadership
51.2
Award applications
50.2
f
179
158
162
148
153
140
135
132
129
123
124
122
122
110
109
116
114
112
112
109
107
M
2.84
2.79
2.76
2.70
2.66
2.65
2.61
2.61
2.61
2.59
2.57
2.57
2.55
2.54
2.55
2.52
2.53
2.52
2.49
2.50
2.48
SD
0.37
0.42
0.43
0.46
0.50
0.49
0.54
0.51
0.50
0.51
0.52
0.52
0.54
0.54
0.51
0.56
0.51
0.53
0.57
0.52
0.55
There were several topics that the majority of agriculture, food, and natural resource
teachers labeled as important to include in teacher preparation programs. It is necessary to note
April 20-23, 2011
that a majority of teachers ranked these topics with a 2 for important. Even though this is not the
highest ranking for topics, this information is included to illustrate which topics the majority of
teachers felt were important. Agricultural economics was the topic that the most teachers agreed
was important (n = 151, 71.9%). Other topics in which the majority of teachers identified as
important (in order from the highest number of teachers to right at a majority of teachers) were
agronomy (n = 149, 71.0%), meat science, engine theory, animal genetics, assessment, state
performance standards, course rotation, horticulture, human growth and development,
floriculture, educational psychology, plant science, agricultural communications, food science,
natural resources, history of agricultural education, interpersonal relations, state curriculum
standards, pedagogy, literacy, legal issues, diversity, advisory committees, fundraising, and
animal nutrition (n = 106, 50.3%). According to mean, the highest-ranking topic teachers
designated as important for inclusion in teacher preparation education was animal nutrition (M =
2.47, SD = 0.53). The lowest ranking topic was floriculture (M = 1.90, SD = 0.61). There were
two topics in which the majority of teachers did not think were very important or important.
These topics were curriculum development and stress management.
Agriculture, food, and natural resource teachers were also asked to identify what
experience best prepared them for their career as an agricultural science teacher in relation to
each topic. The choices were teacher preparation education, teacher in-service, teaching
experience, other professional experience, and the professional development conference. In the
first section of the instrument the most common response for all but one of the 14 agricultural
content topics was teacher preparation education (Table 2). The majority of teachers identified
teacher preparation education as the best experience for animal genetics (n = 115, 55.3%), engine
theory (n = 114, 54.5%), agricultural economics (n = 110, 53.7%), agronomy (n = 110, 53.7%),
and plant science (n = 106, 50.5%). Teacher experience was listed as the best preparation
experience for the topic of agricultural communications, although like many of the other topic
areas none of the experiences were listed by enough respondents to constitute a majority.
Table 2
Best Preparation Practices for Agricultural Content Topics
Topic
f
%
Practice
Animal genetics (n = 208)
115
55.3
Teacher preparation
Engine theory (n = 209)
114
54.4
Teacher preparation
Agricultural economics (n = 205)
110
53.7
Teacher preparation
Agronomy (n = 205)
110
53.7
Teacher preparation
Plant science (n = 210)
106
50.5
Teacher preparation
Animal nutrition (n = 208)
104
50.0
Teacher preparation
General animal science (n = 208)
96
46.2
Teacher preparation
Meat science (n = 208)
96
46.2
Teacher preparation
Horticulture (n = 206)
93
45.1
Teacher preparation
Natural resource management (n = 207)
81
39.1
Teacher preparation
Food science (n = 203)
79
38.9
Teacher preparation
Floriculture (n = 198)
74
37.4
Teacher preparation
Agricultural communications (n = 209)
70
33.5
Teaching experience
Livestock production (n = 208)
67
32.2
Teacher preparation
Note. Percentages are calculated based on the number of respondents for each question.
April 20-23, 2011
When teachers were asked to identify the best preparation experience for each of the
agricultural education topics the same two experiences were most commonly reported (Table 3).
The majority of teachers chose teaching experience as the best preparation for fundraising (n =
118, 59.0%), parent relations (n = 109, 54.0%), public relations (n = 102, 50.5%), and program
management (n = 100, 50.5%). Teacher preparation education was chosen as the best experience
by a majority of the teachers for history of agricultural education (n = 114, 57.3%) and general
agricultural education (n = 109, 56.5%). The professional conference was the most commonly
identified as the best preparation experience for legal issues faced in their careers (n = 72,
36.0%).
Table 3
Best Preparation Practices for Agricultural Education Topics
Topic
f
%
Practice
Fundraising (n = 200)
118
59.0
Teaching experience
History of agricultural education (n = 199)
114
57.3
Teacher preparation
General agricultural education (n = 193)
109
56.5
Teacher preparation
Parent relations (n = 202)
109
54.0
Teaching experience
Public relations (n = 202)
102
50.5
Teaching experience
Program management (n = 198)
100
50.5
Teaching experience
Program structure and planning (n = 201)
96
47.8
Teaching experience
Award applications (n = 199)
94
47.2
Teaching experience
SAEP (n = 201)
94
46.8
Teaching experience
FFA (n = 198)
93
46.8
Teaching experience
Agricultural youth leadership (n = 193)
86
44.6
Teaching experience
Methods of teaching ag. science (n = 197)
85
43.1
Teacher preparation
Leadership (n = 197)
84
42.6
Teaching experience
Record keeping systems (n = 200)
82
41.0
Teaching experience
Organizational leadership (n = 201)
82
40.8
Teaching experience
Legal issues (n = 200)
72
36.0
Professional conference
Agricultural careers (n = 202)
62
30.7
Teaching experience
Interviewing and resume building (n = 202)
62
30.7
Teaching experience
Advisory committees (n = 202)
59
29.2
Teaching experience
The trend from the previous two sections continued when teachers were asked to identify
the experience that best prepared them to deal with the general education topics listed in Table 4.
Teaching experience was most commonly reported as the best preparation experience for 10 out
of the 18 general education topics. The majority of teachers chose this response for course
rotation (n = 97, 50.3%). Teacher preparation education was identified for seven of the topics.
Teacher preparation education was chosen by a majority of the teachers as the best preparation
practice for the topics of educational psychology (n = 109, 56.5%) and pedagogy (n = 101,
53.4%). Diversity in education was unique in that teaching experience and teacher preparation
education tied as the most common response.
April 20-23, 2011
Table 4
Best Preparation Practices for General Education Topics
Topic
f
%
Practice
Educational psychology (n = 193)
109
56.5
Teacher preparation
Pedagogy (n = 189)
101
53.4
Teacher preparation
Course rotation (n = 193)
97
50.3
Teaching experience
Learning cognition and development (n = 196)
97
49.5
Teacher preparation
Human growth and development (n = 195)
96
49.2
Teacher preparation
Classroom management (n = 195)
92
47.2
Teaching experience
Exceptionalities in education (n = 188)
83
44.2
Teacher preparation
Literacy (n = 194)
83
42.8
Teacher preparation
Interpersonal relations in schools (n = 193)
79
40.1
Teaching experience
Curriculum development (n = 195)
78
40.0
Teaching experience
Teaching methods (n = 196)
78
39.8
Teacher preparation
Technology in the classroom (n = 197)
74
37.6
Teaching experience
Assessment (n = 197)
72
37.1
Teaching experience
Time management (n = 193)
69
35.8
Teaching experience
Diversity in education (n = 193)
64
33.2
Tied
Stress management (n = 196)
62
31.6
Teaching experience
State performance standards (n = 193)
58
30.1
Teaching experience
State curriculum standards (n = 191)
56
29.3
Teaching experience
Teacher preparation education and/or teaching experience were chosen as the best
preparation experiences for agriculture, food, and natural resource teaching careers. Out of 51
topic areas there was only one in which the summer development conference was selected as the
best preparation experience by the majority of teachers.
Current agricultural science teachers are the experts on what challenges today‟s
educational climate create for teachers and how to adequately prepare teachers to overcome
those challenges. The agriculture, food, and natural science teachers that completed this survey
are fairly representative of the field. There was a ratio of nearly 3:1 male (72.6%) to female
(27.4%) ratio. The majority of teachers received a bachelor‟s degree (59.5%). As expected,
agricultural education was the most common field listed for an undergraduate degree with 81.3%
of teachers completing a degree in that area. The majority of agricultural science teachers
(64.5%) received their certification through an undergraduate program. A very small percentage,
2.8%, of teachers was certified through their regional education center.
Student teaching was completed by 98.5% of teachers. The other 1.5% of agricultural
science teachers that did not student teach possibly began teaching after another career. Student
teaching was also considered to be very important by a larger number of teachers (76.7%) than
early classroom observation (33.2%). There may not be a large emphasis on early classroom
observation in agricultural science teacher preparation education, and opportunities for learning
provided through that experience might be forgone as a result.
April 20-23, 2011
It would seem that because almost all agricultural science teachers are going through a
student teaching experience, teachers are receiving on-the-job, authentic experience before
entering the field. Agricultural education is founded on experiential learning, so it is rational to
assume that the most learning of how to apply all of the knowledge gained through teacher
preparation education occurs in this time period. Therefore, the small percentage of teachers that
reported they did not student teach seem to be at a huge disadvantage upon accepting their first
positions. It also seems to reason that teachers who reported they did not student teach were
those teachers that were likely to be certified through the regional education center.
There is a long list of topics that the majority of teachers felt were very important for
inclusion in teacher preparation education for agriculture, food, and natural resource teachers.
These topics include FFA, classroom management, leadership, general animal science, time
management, SAEP, agricultural youth leadership, parent relations, general agricultural
education, livestock production, public relations, record keeping, program management,
technology in the classroom, teaching methods, program structure, agricultural careers,
interviewing and resume building, organizational leadership, and award applications. Teachers
feel that all of these topics need to be taught in teacher preparation programs. This list could be a
starting point for university educators who are re-evaluating their teacher education programs.
Agricultural science teachers identified topics, which although not very important, the
majority still agreed were important to include in teacher preparation programs. These topics
included agricultural economics, agronomy, meat science, engine theory, animal genetics,
assessment, state performance standards, course rotation, horticulture, human growth and
development, floriculture, education psychology, plant science, agricultural communications,
food science, natural resources, history of agricultural education, interpersonal relations, state
curriculum standards, pedagogy, literacy, legal issues, diversity in education, advisory
committees, fundraising, and animal nutrition. These topics are important to agricultural teacher
education preparation and should be taught in some form to future educators, although not as
large of an emphasis may need to be placed on these topics.
Many of the topics teachers deemed in this study as very important or important are
consistent with areas identified in previous research as essential for proper teacher preparation
education. These areas included learning styles (which many programs deal with when teaching
the subjects of diversity in education and teaching methods now), technical areas, teaching
methods, and teaching techniques (Dobbins and Camp, 2006). This study was in line with that of
Edwards and Briers (1999) in reporting that facilitating student learning, program management,
personal roles and relationships, leadership, and personal growth. Joerger‟s findings (2002) that
classroom management and technical agriculture were important were also supported.
Teacher preparation education was selected as the best preparation experience for all of
the agricultural content topics except for agricultural communications, for which teaching
experience was selected. Therefore, it may be that teacher preparation education programs are
doing their job in preparing teachers for their future careers in relation to these topics with the
exception of agricultural communications. This exception may be a result of this topic being a
April 20-23, 2011
relatively new and emerging field of study in comparison to when many of the teachers
completed their teacher preparation programs.
Teaching experience was listed most commonly as the experience that best prepared
teachers for their careers for 15 out of the 19 agricultural education topics. This may be due to
the fact that some things cannot adequately and accurately be prepared for in a classroom during
teacher preparation programs. The alternative is that teacher preparation programs are not
providing instruction that meets the needs of future educators in these areas. Teacher preparation
education was listed most commonly for a few of these topics including the history of
agricultural education, general agricultural education, and methods of teaching agricultural
science. It is important to note here that the summer professional development conference was
listed as the experience that best prepared teachers to deal with legal issues in their career. This
area may be incorporated into programs as legal issues are a growing concern in all facets of
education.
General education topics were the most evenly split for the most commonly identified
best preparation practice. Teaching experience was reported as the best teacher preparation
practice for 10 of the 18 topics, while teacher preparation education was the most common
response for seven of the topics. For the topic of diversity in education there was a tie for the
most highly reported best preparation practice between teacher preparation education and
teaching experience.
The above information continues to support the inclusion of student teaching experience
in teacher preparation programs. Teaching experience is obviously an important source of
knowledge in several of the topic areas included in this study. The only way teacher preparation
programs can guarantee an authentic teaching experience is through student teaching.
The first recommendation for research that results from this study is that student teaching
experiences should be further investigated to determine if this experience adequately prepared
them in the topic areas for which they chose teaching experience as the best preparation practice.
Also, a deeper exploration of the correlation between certification method and student teaching
experience would be valuable. It would also be interesting to see whether certification method
had an effect on the perceived importance of topics for inclusion in an agricultural teacher
preparation education program.
Another recommendation for research is to investigate which of the topics deemed highly
important by the majority of agricultural teachers are included in which of the programs used for
review during instrumentation design. Future research could also investigate the reasons for
importance rating. For instance, teachers could be rating importance based on whether they could
learn the information easily outside of teacher preparation education. Determining if availability
of knowledge from other sources plays a role in the perceived importance of including a topic in
teacher preparation education would be beneficial.
The needs assessment should be continued, as this is only the first phase of the needs
assessment. Not only should data collection continue as suggested above, but content knowledge
tests should be given to see if teachers have been adequately prepared in the areas that compose a
April 20-23, 2011
proper agriculture, food, and natural resources teacher education. These areas have been
identified throughout this first phase of the needs assessment that is reported in this particular
study. Students in high school programs should also be surveyed on their perceptions and
attitudes toward their teachers as well as their teachers‟ knowledge level.
Practices in the field of teacher preparation education could be revised at the university
level. The first recommendation for revision is that programs use early classroom observation to
the fullest advantage when preparing agricultural science teachers. The next recommendation is
to require student teaching experience regardless of certification method, as it is the only kind of
teaching experience a preparation program can provide.
As a practitioner in the field of teacher preparation in agricultural education, it would be
valuable to evaluate a program to determine which of the very important topics identified in this
study were actually being taught in university programs. Also, it is necessary to make the same
considerations for topics that were identified as important by the majority of respondents in this
study. Teaching experience is the only way to become adequately prepared to handle certain
situations. Teacher preparation programs should strive to prepare future educators to the best of
their ability for these activities. They should also help provide a strong realistic foundation for
what teachers will face in their careers in regards to this topic.
This study can also be used as a time allocation tool for teacher preparation programs.
More time should be spent on topics considered to be very important by the majority of teachers.
The topics that the majority of teachers deemed to be important should be taught as well;
however, less time could be spent on those topics.
Another issue that should immediately be considered by teacher preparation educators is
that teachers received their best preparation for legal issues they face at a professional
development conference. It is a known fact that not all teachers attend this conference. This topic
should be taught in preparation education, to keep teachers from having to learn from their
mistakes in regard to legalities.
April 20-23, 2011
References
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standards in vocational agriculture. Journal of the American Association of Teacher
Educators in Agriculture, 18(1), 1-8.
Birkenholz, R.J., & Simonsen, J.C. (2009). Characteristics of distinguished programs of
agricultural education. Proceedings from the 2009 American Association for Agricultural
Education Research Conference, 312-325, Louisville, KY.
Crutchfield, N.R. (2010). The relationship of work engagement, work-life balance, and
occupational commitment on the decisions of agricultural educators to remain in the
teaching profession. Unpublished doctoral dissertation, Texas A&M University & Texas
Tech University.
Darling-Hammond, T. (1997). Doing what matters most: Investing in quality teaching. New
York: National Commission on Teaching and America‟s Future.
Dobbins, T. R. & Camp, W. G. (2000). Clinical experience for agricultural teacher education
programs in North Carolina, South Carolina, and Virginia. Proceedings of the 27th
Annual National Agricultural Education Research Conference, 543-555.
Duncan, D. W., Ricketts, J.C., Peake, J.B., & Uesseler, J. (2006). Teacher preparation and inservice needs of Georgia agriculture teachers. Journal of Agricultural Education, 47(2),
24-35.
Edwards, M. C. & Briers, G. E. (1999). Assessing the in-service needs of entry-phase agriculture
teachers in Texas: A discrepancy model versus direct assessment. Journal of Agricultural
Education, 40(3), 40-49.
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Knobloch, N. A., and Whittington, M. S. (2002a). Factors that influenced beginning teachers‟
confidence about teaching in agricultural education. Proceedings of the annual meeting of
the AAAE Central Region Agricultural Education Research Conference, St. Louis, MO.
Knobloch, N. A., and Whittington, M. S. (2002b). Novice teachers‟ perceptions of support,
preparation quality, and student teaching experience related to teacher efficacy. Journal
of Vocational Education Research, 27(3), pp. 331-341.
Miller, W. W., Kahler, A. A. & Rhealt, K. (1989). Profile of the effective vocational agriculture
teacher. Journal of Agricultural Education 30(2), 33-40.
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Mundt, J. (1991). The induction year: A naturalistic study of beginning secondary teachers of
agriculture in Idaho. Journal of Agricultural Education, 32(1), 18-23.
National Commission on Teaching and America‟s Future. (1996). What matters most: Teaching
for America’s future. New York: Author.
National Research Council. (1988). Understanding agriculture: New directions for education.
Washington, DC: National Academy Press.
Nunnally, J.C. (1967). Psychometric theory. New York: McGraw-Hill Book Company, Inc.
Osborne, E.W. (Ed.) (n.d.). National research agenda: Agricultural education and
U.S. Department of Education. (1997). Characteristics of stayers, movers, and leavers: Results
from the teacher followup survey: 1994-95. Washington, DC: National Center for
Educational Statistics.
Witkin, B.R., and Altschuld, J.W. (1995). Planning and conducting needs assessments: A
practical guide. Thousand Oaks, CA: Sage Publications, Inc.
April 20-23, 2011
Out in the Cold About COOL: An Analysis of U.S. Consumers’ Awareness of Mandatory
Country-of-Origin Labels for Beef
Katie Allen, Courtney Meyers, Todd Brashears, & Scott Burris
Abstract
Mandatory country-of-origin labeling (COOL) is a food policy that requires many fresh foods to
carry a label noting the country or countries where the product was born, grown, slaughtered,
and processed. While many have favored the policy as a new marketing tool, others have
criticized the program as confusing, expensive, and difficult to mandate. An online survey of U.S.
beef consumers who were also the primary household grocery buyers (N=396) was conducted to
examine their knowledge and awareness of COOL and information sources used to make foodpurchasing decisions post-implementation of mandatory COOL. Only 10 respondents (2.5%)
knew that COOL stood for country-of-origin labeling, and 287 respondents (72.5%) indicated
they had never heard of COOL. Despite an apparent lack of knowledge and awareness of the
policy, a majority of the participants still supported the idea of mandatory COOL and preferred
to have the label on their beef. The results indicated more consumer education is needed about
COOL, trade, and food safety issues. Further research is necessary to examine this new policy as
it diffuses through a system, and qualitative research could help to understand how to better
educate and communicate messages to consumers about COOL.
Introduction
Consumers in the United States have more options today when purchasing food based on
their specific wants and needs. When food shopping, consumers often look for distinguishing
features, such as brands, labels, store signs, and unique packaging, to select one food item from
the many available (Schupp & Gillespie, 2001). Food recalls and cases of food-borne illness
have also influenced how consumers decide what to purchase. These issues have raised questions
about the role country-of-origin labels, traceability, and food safety inspections have in shaping
consumers’ perceptions of food safety and quality worldwide (Loureiro & Umberger, 2007).
Specifically in the United States, various agricultural and consumer advocacy groups
have argued and pushed legislation for country-of-origin labeling (COOL) to alleviate food
safety concerns and garner support for U.S. products (Krissoff, Kuchler, Nelson, Perry, &
Somwaru, 2004). Srivastava (2003) reported three reasons the U.S. government considered
mandatory traceability for food: 1) to protect consumers from fraud and producers from unfair
competition, 2) to facilitate and monitor the food chain to enhance food safety, and 3) to address
consumer information gaps about food safety and quality. The mandatory U.S. COOL program
derived as a result of objectives such as these and created a system in which consumers have
more buying power (Quittner, 2007).
U.S. lawmakers created the interim final ruling for mandatory COOL on August 1, 2008,
and instituted that ruling on September 30, 2008. The final mandatory ruling for COOL went
1
April 20-23, 2011
into effect in March 2009 (Bjerga, 2009). The final rule outlined the requirements for labeling
covered commodities and the recordkeeping requirements for retailers and suppliers. Specific
criteria determined if a product can bear a “United States country of origin" declaration, or if it
must be labeled as foreign origin or have a multi-country-of-origin label (USDA, 2009a).
Prior to the implementation of mandatory COOL in the United States, other labeling
programs, such as organic labeling for milk, have gained consumer acceptance (Kiesel & VillasBoas, 2007). Likewise, former studies have found that consumers favor the idea of mandatory
COOL in the United States and are willing to pay more for COOL for beef (Dickinson & Bailey,
2005; Loureiro & Umberger, 2003; Schupp & Gillespie, 2001). Research has also shown that
most consumers would prefer U.S.-labeled beef over beef labeled from another country or
labeled with a multi-country-of-origin label (Loureiro & Umberger, 2003).
Mandatory COOL in the United States means more notification for consumers on where
their food comes from, but the controversial program has also drawn resistance from some who
say it requires too much time, work, and money. Implementing the program might have also
caused some confusion among consumers (Siegrist, 2009). According to Rogers’ (2003)
diffusion of innovations theory, complexity adversely affects the adoption of an innovation in a
social system. Although many people have supported COOL as a method to improve food safety,
the true purpose of COOL has been met with differing ideas by government officials, commodity
and consumer groups, and the media, thus making it a more complicated issue. The American
Farm Bureau Federation (AFBF, 2007) said that COOL is a marketing program meant to provide
people with more information, but most people perceive it as a food safety or animal health
issue. Likewise, USDA leaders have also held strong to their notion that the purpose of COOL is
not for improving food safety but for marketing U.S. beef (Bjerga, 2009).
Inconsistent labeling might also generate confusion among consumers. The label for beef
begins with the country where the animal was processed, or slaughtered, and then the retailers
are responsible for listing other countries of origin on the label in alphabetical order (Kay,
2008b). However, some food retailers are adopting a catch-all blanket label for beef to minimize
costs, which includes all the countries from which the product could have potentially come. This
label is placed on all products, regardless of actual origin, so the use of the “Product of U.S.”
label for beef might be more limited than supporters of COOL had hoped. The USDA is
combating this by requiring beef from the United States to be labeled as U.S. beef, rather than
allowing a blanket statement (Hagstrom, 2008).
Another criticism of COOL is that the program is expensive to implement and maintain.
Government leaders have estimated the program would cost between $500 million and $3.9
billion in its first year and subsequent year expenses to run between $140 million and $600
million (AFBF, 2007). COOL opponents argue the costs for a more accurate record-keeping
system would pass to the consumer and raise food prices (Krissoff et al., 2004).
Maintaining international trade relations poses a concern of the COOL program as well.
Because the program requires more record keeping, U.S. beef and pork companies are either
refusing to buy or are putting more emphasis on segregating cattle and hogs from outside the
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April 20-23, 2011
United States (Burgdorfer, 2009). In October 2009, officials from Canada and Mexico contacted
the World Trade Organization (WTO) and claimed COOL was damaging North American trade
(Lynn, 2009). Many livestock producers and industry experts say consumers do not care about
the country of origin or pay attention to the labels, and the added cost of implementing the
program is hurting the meat industry (Burgdorfer, 2009).
On average, a U.S. consumer eats 67 pounds of beef per year (Davis & Lin, 2005). The
USDA reported the retail value of beef in the United States in 2008 at $76 billion (USDA,
2009b). As beef is an important agricultural commodity and food source, the debate among
lawmakers and agricultural and consumer groups focusing on how COOL affects the beef
industry in particular has been continuous. U.S. cattle feeders and meat packers, processors, and
retailers have generally opposed required country-of-origin labeling (Krissoff et al., 2004).
Mandatory COOL for the beef industry, according to the USDA, is expected to cost cattle
producers $9 more per head, packers and wholesalers $1.50 more per pound of beef, and retailers
about $7 more per pound of beef (Kay, 2008a).
COOL in the United States is a new program that affects many in the agricultural
industry; therefore, it is important to examine the effectiveness of the labeling system from the
consumers’ perspective to determine its usefulness. As with any new innovation, COOL will
take time to diffuse through a system. Diffusion is defined as “the process in which an
innovation is communicated through certain channels over time among members of a social
system” (Rogers, 2003, p. 5). COOL is an authority-influenced innovation, which means
relatively few individuals in a system who possess power—in this case, U.S. lawmakers—make
the decision to adopt. Rogers’ diffusion of innovations theory was used to help create an
understanding of how information about COOL has been received among consumers and if
consumers have adopted the new label when purchasing beef.
The National Research Agenda (NRA): Agricultural Education and Communication
2007-2010 (Osborne, n.d.) identifies the need to understand what information various
stakeholders need to make informed decisions. The purpose of this study was to explore U.S.
beef consumers’ knowledge and awareness toward country-of-origin labels following the
implementation of mandatory COOL in the United States. The following research questions were
used to guide the study:
1.
2.
3.
4.
What are the demographic characteristics of the sample?
What are the information sources consumers use to make food purchases?
How aware are U.S. consumers of COOL?
What are the relationships between consumer demographics, COOL awareness, and
the information sources consumers use to make food purchases?
3
April 20-23, 2011
This study used a descriptive survey design by means of a questionnaire administered
online by Zoomerang™ to a nationwide sample of U.S. primary household grocery buyers.
Zoomerang™ was able to administer the questionnaire only to people who had indicated they
were the primary household grocery buyer. Targeting this specific sample on a national scale
using any other method was not feasible, if not impossible. According to Zoomerang™ (2010),
its more than two million survey respondents are profiled using more than 500 demographic,
lifestyle, occupational, and geographic attributes, which gives researchers access to specific
target groups, such as U.S. primary household grocery buyers. Therefore, the accessible
population was individuals in Zoomerang™’s online survey panel who had indicated, on an
extensive personal disclosure, that they are the primary household grocery buyer.
As this survey was a national assessment, the entire population of the United States was
taken into account to determine sample size. The U.S. Census Bureau estimated the total U.S.
population in December 2009 at more than 308 million (U.S. Census Bureau, 2009). According
to the Krejcie and Morgan (1970) table for required sample size, a population size of more than
300 million requires a sample size of 384 participants with a 95% confidence, 5% margin of
error. Zoomerang™ charges by the number of respondents, meaning that when a certain number
is reached, access to the online questionnaire is closed. This method provided the quota sample
of U.S. primary household grocery buyers.
The respondents were asked at the beginning of the questionnaire if they or anyone in
their household consumed beef or other meat products. If the respondents answered “no,” they
were directed to complete the demographics section only, and their responses were not used
when analyzing the results for this study. Only those people who indicated they, or someone in
their household, consumed beef were used to ensure the collected data were from beef
consumers. A total of 413 people completed the online questionnaire before Zoomerang™ closed
access. Of the completed questionnaires, 17 claimed to not be consumers of beef. Therefore, the
sample used for this study included 396 respondents.
A researcher-developed questionnaire was administered online to collect data to address
the research questions. The instrument was tested for validity using a panel of experts and
reliability using a pilot test of 30 participants before Zoomerang™ administered the
questionnaire to the sample. The first section of the instrument consisted of questions related to
the research variables of interest. The second section of the instrument asked demographic
questions only. Items in the first section consisted of three yes-or-no questions, 12 multiple
choice questions, seven multi-item Likert-type scale measures using five-point scales, three
questions that allowed participants to check all that applied, and two open-ended questions.
Items in the second section included one yes-or-no question, 10 multiple-choice questions, and
one open-ended question. Once the survey was complete, data analysis was conducted using
SPSS® version 17.0 for Windows™. The researchers found common themes in the open-ended
answers and calculated frequencies for those answers.
4
April 20-23, 2011
Findings
Research Question 1: What are the demographic characteristics of the sample?
The sample for this study included 396 respondents. Demographic questions asked
participants to disclose or classify a number of characteristics. The items reported in this paper
are gender, age, highest level of education obtained, state of residence, estimated annual
household income, ethnicity, and level of involvement in the beef industry and agricultural
industry. More females (n = 268, 67.7%) responded to the survey compared to males (n = 128,
32.3%). Respondents’ ages ranged 66 years, from 18 to 84, with a mean age of 48.63 (SD =
14.33). While education ranged from less than a high school education (n = 4, 1%) to a doctorate
degree (n = 6, 1.5%), most respondents indicated they had some college education (n = 115,
29%) or a bachelor’s degree (n = 100, 25.3%).
Respondents reported residing in 42 U.S. states. Most respondents said they reside in
California (n = 75, 18.9%), followed by Texas (n = 34, 8.6%), and New York (n = 30, 7.6%).
The eight states not represented by the sample included Alaska, Idaho, Maine, Nevada, New
Hampshire, North Dakota, Rhode Island, and South Dakota. Income levels ranged from less than
$15,000 annually to more than $105,000 annually, with most respondents making between
$45,000 and $59,000 per year (n = 69, 17.4%). Most survey respondents were Caucasian (n =
332, 83.8%). On a five-point Likert-type scale (1 = not at all, 5 = quite a lot), respondents
indicated they have a fairly low involvement in both the agricultural industry (M = 1.62, SD =
1.03) and beef industry (M = 1.54, SD = 0.94).
Research Question 2: What are the information sources consumers use to make food purchases?
Participants could check all the resources they use to make food purchases from a
provided list (family and friends, Internet, newspaper, magazine, radio, supermarket
advertisement, and television), as well as disclose other resources they use that were not on the
provided list. Supermarket advertisements were used by the largest percentage of respondents (n
= 244, 61.6%). Half of the respondents (n = 198, 50%) said they also get information from
family and friends. Traditional information sources were also mentioned: newspaper (n = 122,
30.8%), Internet (n = 105, 26.5%), television (n = 98, 24.7%), magazine (n = 55, 13.9%), and
radio (n = 21, 5.3%). In addition to the provided responses, 40 respondents (10.1%) said they
used other sources of information to make food-purchasing decisions, including personal
experiences (n = 11, 2.8%), the store itself and its employees (n = 10, 2.5%), and the product
labels (n = 4, 1%).
Research Question 3: How aware are U.S. consumers of COOL?
The first question asked participants if they knew what COOL stands for in regard to
food labeling to initially assess knowledge of COOL before it was explained in further detail
later in the questionnaire. Seventy-three respondents (18.4%) said they did know what COOL
stands for, while 323 (81.6%) said they did not know. Respondents were then asked to provide
5
April 20-23, 2011
an explanation of what COOL stands for. Of the 72 respondents who elaborated, 10 (2.5%)
reported COOL stands for country-of-origin labeling. Most respondents (n = 47, 11.2%) who
elaborated said COOL was related to temperature or keeping products refrigerated or frozen.
When asked if they have ever noticed the country-of-origin label on their purchased beef
products, 110 respondents (27.8%) said yes, and 286 respondents (72.2%) said no. Respondents
were then asked to explain where they had seen the country-of-origin labels located on the
products. Of the 112 respondents who elaborated, most said they had seen the country-of-origin
label on the front of the package (n = 24, 21.4%), 20 (17.9%) said on the backside or bottom of
the package, and 11 (9.8%) said the label was somewhere on the package in fine, small, or hardto-read print. Thirteen respondents (11.6%) did not recall exactly where the country-of-origin
label was located, and nine respondents (8%) reported seeing the label in many different places,
including the top and bottom of the package and on the store meat case. Survey participants were
also asked to think about the last beef product they purchased then indicate from which country
or countries that product originated on a list including the United States and its top 10 beef
importers (Table 1). Twelve respondents indicated at least one country of origin for their last
purchased beef product and also selected “don’t know.”
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April 20-23, 2011
Table 1
Country-of-Origin for Last Beef Product Purchased by Respondents (N = 396)
Country
Frequency
Percentage
United States
216
54.5
Don’t know
179
45.2
11
2.8
New Zealand
9
2.3
Mexico
8
2.0
Argentina
6
1.5
Australia
4
1.0
Brazil
2
0.5
Costa Rica
1
0.3
Honduras
1
0.3
Nicaragua
1
0.3
Other
1
0.3
Canada
Uruguay
0
0.0
Note. Mode = United States. Respondents could check multiple answers; percentages do not
equal 100%.
While information sources used to making food-purchasing decisions were assessed in
research question two, the information sources respondents used to find out about COOL
specifically was examined within this research question. When asked to check all the resources
that provided them with information about COOL, most respondents said they had not heard of
COOL (n = 287, 72.5%). If respondents had heard of COOL, the most common resource was the
Internet (n = 36, 9.1%). Table 2 provides the frequencies and percentages of each source. Twelve
respondents provided other resources for COOL not included in the list. The most common other
response was that this survey was the first time they had heard of COOL (n = 4, 1%).
7
April 20-23, 2011
Table 2
Resources Providing Information About COOL (N = 396)
Resource
Frequency
Percentage
287
72.5
Internet
36
9.1
Don’t know
25
6.3
Television
24
6.1
Family/Friends
21
5.3
Newspaper
19
4.8
Supermarket advertisement
13
3.3
Other
12
7.8
Radio
10
2.5
Have not heard of COOL
Magazine
9
2.3
Note. Mode = Have not heard of COOL. Respondents could check multiple answers; percentages
do not equal 100%.
When asked if they had heard of mandatory COOL in the past year, 381 respondents
(80.3%) said they never heard of mandatory COOL. Fifty respondents (12.6%) said they had
heard of COOL once, 21 respondents (5.3%) had heard of COOL 2-5 times, and seven
respondents (1.8%) had heard of COOL more than five times. On a five-point Likert-type scale
(1 = not at all, 5 = quite a lot), respondents indicated they were not very aware of labeling
policies for beef (M = 2.17, SD = 1.08) and COOL for beef (M = 1.76, SD = 1.07).
After analyzing initial awareness of COOL, participants were asked to rank the
importance of having a country-of-origin label on four commonly purchased beef cuts: ground
beef, roast, steak, and stew meat using a five-point Likert-type scale (1 = not at all, 5 = very).
Respondents put a relatively high importance on having a country-of-origin label on ground beef
(M = 4.25, SD = 1.02), roast (M = 4.19, SD = 1.01), steak (M = 4.23, SD = 1.00), and stew meat
(M = 4.18, SD = 1.05).
Research Question 4: What are the relationships between consumer demographics, COOL
awareness, and the information sources consumers use to make food purchases?
8
April 20-23, 2011
Correlations were performed to determine the relationships between selected
demographics, COOL awareness, and the information sources consumers use to make food
purchases. The strength of the relationships was reported based on Davis (1971): 1.00 perfect
relationship, .70-.99 very high relationship, .50-.69 substantial relationship, .30-.49 moderate
relationship, .10-.29 low relationship, and .01-.09 negligible relationship. Significant
relationships found at .05 a priori are noted within the tables.
Table 3 shows the relationships between involvement in the agricultural and beef
industries and respondents’ self-perceived knowledge of what COOL stands for, as well as selfperceived awareness of both labeling policies in general and COOL for beef. All relationships in
Table 3 are positive and significant. Knowledge of what COOL stands for and industry
involvement showed low relationships, while awareness of COOL and labeling policies and
industry involvement showed substantial relationships.
Table 3
Relationships Between Industry Involvement and Knowledge/Awareness
Ag industry
involvement
Characteristic
Knowledge of what COOL stands for (rpb)
Beef industry
involvement
.12*
.11*
.52*
.55*
.54*
.53*
Awareness
Labeling policies for beef (r)
COOL for beef (r)
Note. * p < .05.
Table 4 shows the relationships between information sources used for COOL and
agricultural and beef industry involvement. All relationships are low; however, “have not heard
of COOL” and agricultural (rpb = -.20) and beef industry (rpb = -.20) involvement are the only
negative relationships reported. The strongest associations were between agricultural (rpb = .35)
and beef industry (rpb = .29) involvement and use of magazines as a resource for COOL. These
were both moderate, positive relationships.
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April 20-23, 2011
Table 4
Relationships Between Industry Involvement and Information Sources Used for COOL
Ag industry
Beef industry
Information source
involvement (rpb)
involvement (rpb)
Don’t know
.07
.06
-.20*
-.20*
Family/Friends
.23*
.23*
Internet
.20*
.22*
Newspaper
.18*
.17*
Magazine
.35*
.29*
Radio
.19*
.18*
Supermarket advertisement
.08
.12
Television
Note. * p < .05.
.03
.03
Have not heard of COOL
Table 5 shows the relationships between sources of information, awareness of labeling
policies, and awareness of COOL. There was a low, negative correlation between perceived
knowledge of COOL and “have not heard of COOL” (φ = -.17), which was significant at alpha
level .05 and was the only negative relationship in the column. The relationship between
awareness of labeling policies and “have not heard of COOL” was a low, negative relationship
(rpb = -.25) significant at alpha level .05. The relationship between “have not heard of COOL”
and perceived awareness of COOL was a moderate, negative relationship (rpb = -.41) significant
at alpha level .05. The other information sources showed positive relationships with perceived
knowledge and awareness variables, and many were significant at alpha level .05. Awareness of
COOL overall had stronger relationships with the information sources for COOL.
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April 20-23, 2011
Table 5
Relationships Between Knowledge/Awareness and Information Sources Used for COOL
Knowledge of
Awareness of
Awareness of
Information source
COOL (φ)
labeling policies (rpb)
COOL (rpb)
Don’t know
.04
.05
.12*
-.17*
-.25*
-.41*
Family/Friends
.18*
.22*
.30*
Internet
.17*
.23*
.33*
Newspaper
.20*
.16*
.26*
Magazine
.23*
.29*
.37*
Radio
.21*
.18*
.29*
Supermarket
advertisement
.06
.20*
.17*
.07
.13*
.27*
Have not heard of
COOL
Television
Note. * p < .05.
Conclusions and Recommendations
The sample used in this research study was a quota sample of primary household grocery
buyers in the United States, so results cannot be generalized to the entire population of U.S.
primary household grocery buyers. Because the researchers administered a questionnaire online,
it was more difficult to get a diverse demographic sample; however, many aspects of the
demographics section reported by respondents were very diverse given the nature of the online
survey methodology used. The demographics of the sample were compared to the data from the
latest census by the U.S. Census Bureau, taken in 2000 and reported in 2002.
First, twice as many women responded to the survey, but it was expected that more
women would respond, as the study targeted primary household grocery buyers. In Loureiro and
Umberger’s (2003) study of COOL, they found females are normally the household grocery
shoppers. Respondents in the current study were primarily Caucasian (n = 332, 83.8%), which is
not representative of the U.S. population (75.1%) (U.S. Census Bureau, 2002). Respondents’
ages were more diverse, ranging 66 years, with a mean age of 48.63 (SD = 14.33), which is
above the U.S. average age of 35.3 years. Education level was also diverse, as it ranged from less
than a high school education to a completion of a doctorate degree, with most respondents
indicating they had some college education or a bachelor’s degree. The latest U.S. Census
11
April 20-23, 2011
showed 21% of U.S. citizens having some college education but no degree, and 15.5% holding a
bachelor’s degree. The sample, therefore, had obtained slightly more education overall compared
to education levels of the U.S. population. Respondents also reported residing in different areas,
as they represented 42 of 50 U.S. states. Income levels were comparable to the latest U.S. Census
data. Most respondents (17.4%) indicated they make between $45,000 and $59,000 per year. The
latest U.S. Census showed most people (19.5%) made between $50,000 and $74,000 annually.
Respondents had low involvement in agriculture and the beef industry. This was not surprising,
because so few people in the United States remain directly involved in agricultural production.
When making food-purchasing decisions, respondents most frequently used supermarket
advertisements and family and friends. At the beginning of the questionnaire, participants were
asked if they knew what COOL stands for in regards to food buying. It was evident respondents
do not know what the COOL acronym stands for or were confused by the question. When asked
to explain what they thought it meant, only 10 (13.7%) reported COOL stands for country-oforigin labeling while 47 (64.4%) said COOL was related to temperature or keeping products
refrigerated or frozen. Nearly three-quarters of the respondents said they had not noticed the
country-of-origin label before when purchasing beef products. Respondents who had noticed the
label reported seeing country-of-origin labels in many different and inconsistent places on the
beef products, such as the top or bottom of the package. These differences could be attributed to
the exact location of the country of origin on the label package not being mandated, and
therefore, is inconsistent.
When asked to indicate from which country or countries the last beef product they
purchased had originated, most respondents reported the United States or they did not know.
More respondents indicated their last beef product originated in the United States (n = 216),
compared to the number of respondents who said they had noticed the country-of-origin label (n
= 110) on the last beef product they purchased. Perhaps some of the respondents simply assumed
their last product purchased was a U.S.-origin product.
Most respondents said they had not heard of country-of-origin labeling (n = 287, 72.5%).
If respondents had heard of COOL, the data showed they used a combination of interpersonal
and mass media resources to find out about COOL. Although supermarket advertisements were
the most utilized resource for making food purchases, very few respondents heard about COOL
from a supermarket advertisement. Interestingly, a few respondents said the survey they were
completing was the first time they had heard of COOL. Despite the variance in the information
sources used to find information about COOL, most respondents admitted they were still
unaware of the policy more than 11 months after it was implemented in the United States.
Although most respondents had not heard of COOL and were not aware of the label on their
beef, they still put a relatively high importance on having the label on their ground beef, roast,
steak, and stew meat.
As involvement in the agricultural and beef industries increased, perceived knowledge of
what COOL means also increased; therefore, those with more involvement in agriculture and
beef were more likely to say they knew what COOL stood for and the more they believed they
knew about COOL for beef and beef labeling policies. When examining the relationships
12
April 20-23, 2011
between sources used to get information about COOL and respondents’ involvement in the
agricultural and beef industries, the use of magazines to get information about COOL showed the
strongest relationship with agricultural and beef industry involvement. This indicates that people
involved in the agricultural and beef industries were more apt to hear about COOL from an
agricultural magazine. Prior studies have found that people involved in agriculture rely on farm
publications for information (Ford & Babb, 1989; Wadud, Kreuter, & Clarkson, 1998; Naile,
2006).
Overall, respondents in this study were not very knowledgeable or aware of COOL, but
they still believed COOL is an important concept. The level of perceived awareness of beef
labeling policies and COOL for beef was also low. These findings justify the need for
practitioners to provide a more accurate description about COOL in their communication efforts.
Policy and industry leaders alike need to provide a more focused description of the policy when
working with the media and in their own communications.
Once a more uniform message is developed about COOL and labeling is consistent on
food products, consumer education about COOL will likely see more success. If COOL is meant
to be a marketing tool for U.S. products, the USDA should consider an extensive marketing
campaign for U.S. products such as one implemented in Australia (see Juric & Worsley, 1998).
Policy makers and implementers need to be aware that marketing U.S. products will not likely
help alleviate trade barriers produced by COOL, especially with the United States’ North
American trade partners who have reported already noticing a decline in their U.S. exports.
Communicators should focus on the most utilized communication outlets—supermarket
advertisements and family and friends—to provide consumers with more information about
COOL for beef. Providing more information about COOL for beef might make consumers more
knowledgeable and aware of COOL, but perhaps more importantly, it can also help clarify the
purpose of the policy and decrease the amount of confusion.
As mandatory COOL is a complex issue new to the agricultural and food industries, it is
vital that researchers continue to study this important policy. This study focused strictly on beef,
while COOL applies to a wide variety of fresh foods; therefore, there are many opportunities to
study COOL as it relates to other food products. The diffusion of innovations theory (Rogers,
2003) helped create an understanding as to how food labels can be studied as an innovation
adopted within a social system. As COOL progresses through the steps of the diffusion process,
more research is needed at the various levels to assess its progress and use. As shown in this
study, consumers use many different methods to obtain information, and the information they
have received about the purpose of COOL has been contradictory. A closer examination of
consumer perceptions of COOL and the information sources they utilize is needed as COOL
policy is potentially adjusted based on the concerns of consumers, the food marketing chain,
government and political leaders, and the vital world trade partners of the United States.
Research should be done to specifically find how opinion leaders within social systems are
influencing consumers’ knowledge, awareness, and perceptions of COOL and if these people
have a strong impact on consumers’ purchasing decisions. COOL could be studied in greater
detail using qualitative methods to make more sense of consumers’ knowledge, awareness, and
perceptions of COOL and how these factors motivate food purchases.
13
April 20-23, 2011
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1
Perceived Factors Influencing High School Student Participation in an Integrated
Statewide Dual Credit Program: An Examination of Program Success within the College
of Agricultural and Life Sciences at the University of Idaho
Dr. Allison J. L. Touchstone, Senior Instructor
Dr. Russell A. Joki, Professor
Dr. Lou E. Riesenberg, Professor
University of Idaho
Abstract
Dual credit programs have become increasingly popular with 71% of public high schools
offering courses in 2002-2003. As popularity has grown, so have concerns regarding academic
rigor, course quality, and effects on higher education. The College of Agricultural and Life
Sciences partnered with the state agriculture teachers’ association and state division of
professional technical education to design a dual credit program based on nationally identified
quality programs. Constructivist leadership theory was used in the development of the program
to maintain quality instruction and rigorous content throughout the 2008-2009 school year.
Seven courses were developed, aligned with state pathways, and 156 students earned 307
university semester credits. This quantitative study identified program participants’ perceptions
regarding individuals influencing program decisions and program impact on future success.
The study provided insights to participant perceptions regarding individuals influencing
program participation, and perceived impact of the program on success after high school.
Findings included: agriculture instructors had the greatest impact on student participation and
participants deemed the program would have a large impact on success after high school.
Recommendations for further research included annual replication of this study and impact of
distance education technology on dual credit programs.
Introduction and Conceptual Framework
Introduction
With the increased demand for higher education and the improved alignment and connection
between secondary and post secondary education, dual credit courses have increased
dramatically in the last 15 years. The National Center for Education Statistics found that in
2002-03, nearly 71% of public high schools in the United States offered dual credit courses
(Waits, Setzer, Lewis, & Greene, 2005), and dual credit programs provided post secondary
connections used to increase the rigor of the senior year (Karp, Calcagno, Hughes, Jeong, &
Bailey, 2007). States have established dual credit programs for reasons including:
1. Fostering relationships between secondary and post secondary programs;
2. Enhancing secondary and post secondary efficiency;
3. Implementing rigorous curricula for all students;
4. Increasing post secondary attainment rates; and
5. Reducing the number of students in remedial coursework (Kruegar, 2006).
As of 2006, programs such as dual credit were in place in 47 states (Kruegar, 2006). Dual credit
programs were considered an asset to the educational process (Smith, 2007), and a variety of
outcomes were available for secondary students in these programs:
April 20-23, 2011
2
1. Opportunity to enroll in college-level work while still in high school;
2. Opportunity to earn up to one semester of college credit prior to (or immediately
following) high school graduation; and
3. Opportunity to earn up to one year of college credit prior to (or immediately
following) high school graduation (Andrews, 2004).
Participation in dual credit programs also seemed to be of high quality as 73 % of participants
identified the dual credit course as “better than” or “as good as” the on-campus course the
students took during their college education (Marshall & Andrews, 2002). Marshall and
Andrews (2002) also found that dual credit programs saved participants an average of 1.18
semesters during their college careers as well as providing a seamless Pre-K-16 education
(Kruegar, 2006), and this reduction of time to graduation translates into savings in dollars spent.
In an effort to provide continued rigor and relevance of the senior year and addressing similar
national concerns (Kruegar, 2006), the Idaho State Board of Education defined four methods of
post secondary connections with secondary schools: 1) Dual Credit; 2) Advanced Placement, 3)
Tech Prep, and 4) International Baccalaureate (Idaho State Board of Education Governing
Policies and Procedures, 2009). The increased rigor and relevance as well as secondary to post
secondary connections directly support the National Agricultural Education and Communication
Research Agenda research priority area of Agricultural Education in Schools and Agricultural
Education in University and Postsecondary Settings (Osborne, n.d.).
The conceptual framework of this study was based around constructivist learning, defined as a
social endeavor, indicating that community (in the form of Team Ag Ed) was essential for
learning to occur (Lambert, et al., 1995). Another aspect of constructivist leadership was
developing the means through which an educational community could construct school change
(p. 52), and this common purpose supported a conceptual framework for change paradigms
(p. 57). Teaching in more constructivist, meaning-centered, contextualized ways allowed
students to be better prepared to understand the “deeper constructs underlying practice” (Grubb
& Lazerson, 2005b, p. 17) of the educational process and content.
Constructivist leadership theory indicated the importance of reciprocal relationships among
students, university faculty, and secondary teachers in the educational setting (Lambert, et al.,
1995). Reciprocal processes were understood as those that
 Evoked potential in a trusting environment;
 Reconstructed old assumptions and myths;
 Focused on the construction of a meeting; or
 Framed actions that embody new behaviors and purposeful intentions (Lambert, et. al,
1995, p. 36).
Post secondary connection programs had the potential to develop reciprocal relationships among
stakeholders in which all stakeholders have equal stature in the conversation and aid educational
leaders in developing educational patterns that would best meet the needs of all involved. In this
manner, the stakeholders developed meaning in an educational community (Lambert, et al.,
1995). Coupling constructivist leadership theory with the consistent emphasis on connections
April 20-23, 2011
3
between secondary career and technical education programs and post secondary education (Carl
D. Perkins career and technical education improvement act of 2006, 2006), contextual learning
in the secondary setting provided relevance for curriculum, provided practical application for
information, and established a pathway to post secondary studies (Engberg & Wolniak, 2010).
With the advent and proliferation of online education, many post secondary options were
available to student at the time of this study, including online coursework, professional-technical
education schools, and proprietary schools, as well as the traditional college experience. In
addition, with the increasing costs of post secondary education, parents and students have been
seeking opportunities to minimize post secondary education costs (Harris, 2006; Kruegar, 2006;
Marshall & Andrews, 2002) including shortening the length of time from entrance to graduation
(Kruegar, 2006). Considering potentially shorter length of enrollment in post secondary
programs, competition among programs and institutions offering post secondary connections was
increasing as institutions sought ways to maintain revenue by increasing enrollment, as students
sought to complete and graduate as soon as possible. Additionally, with increased competition
and the foreshadowing of declining enrollments and resources due to the recent global economic
crisis, colleges and universities have been seeking predictive enrollment information to assist
with strategic enrollment and recruitment planning. Based on the need for additional
connections from secondary to postsecondary education within agricultural education, dual credit
programming was developed within the state, implemented, and a follow up study was
conducted to assess the program as a whole.
The purpose of this study was to identify and examine salient variables related to a specific dual
credit program as perceived by first year participants and to analyze various perceived aspects of
those variables to dual credit programs for the providing higher education institution.
Significance and Objective of the Study
This was a quantitative study of a newly developed dual credit program that investigated a
number of variables significant to the success of the program as perceived by the program’s
student participants. It also sought to explore aspects of that dual credit program that might be
advantageous to the higher education institution, including how the program might influence
participants’ university and specific college/curriculum enrollment decisions.
Research Objective
The primary research objective of this study was to determine the factors influencing high school
student participation in the identified dual credit program to provide student feedback to the Dual
Credit Program and complete the Constructivist Leadership feedback loop.
The data collected addressed the following specific aspects of the research objective:
a. determine the perceived impact of the specifically studied dual credit program on post
secondary success of participants;
b. ascertain the frequency of individuals identified as providing information to program
participants;
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4
c. describe the participant enrollment in dual credit program pathways available;
d. describe the perceived impact the participation in the dual credit program had on
participants;
e. ascertain the correlation between gender of dual credit program participants and
above identified aspects of the primary research objective; and
f. ascertain the correlation between the secondary school size attended by dual credit
program participants and above identified aspects of the primary research objective.
Population and Sample
The College of Agricultural and Life Sciences (CALS) Dual Credit program was initiated in the
2008-2009 academic year and involved 133 students from 33 secondary agriculture programs in
33 different school districts across the state. Given the small size of the population, all students
who enrolled in the Dual Credit Program in the initial year were invited to participate in the
study (Gay & Airasian, 2003). Of the 83 permission forms received, 79 students provided viable
e-mail addresses for contact regarding the study for a total of 59 % of the total population. Of
the 79 members of the sample, 2 participants opted out (2.5 %), 26 did not respond (32.9 %), and
53 completed or partially completed the survey for a 67.1 % response rate from the final sample
and a 40 % response rate from the population.
Research Approach
Quantitative research was defined as scientific investigation that includes both experiments and
other systematic methods that emphasize control and quantified measures of performance
(Proctor & Capaldi, 2006), and quantitative researchers are interested in testing hypotheses and
generating models and theories to explain behavior (Hoy, 2010). A quantitative approach was
deemed the most appropriate to assess effectiveness of the program and to gather information
regarding the level of influence a variety of individuals exerted on program participants. The
quantitative approach provided a means to consistently compare perceived effectiveness and
influence on educational choices of the participants. Previous research has also indicated a need
to follow up with students regarding the role of dual credit programs in assisting effective
transitions into the university setting (Kruegar, 2006). The Idaho State Board of Education
(2009) has required follow up studies regarding dual credit programs in Idaho.
Limitations
The limitations of a study were defined as the potential weaknesses or problems with the study
identified by the researcher (Creswell, 2008). The following limitations were identified:
1. Course enrollment distribution by students was limited by the area of affiliation of the
local secondary teacher at the respondent’s home high school;
2. Participants in the study were limited by the choice of the local secondary instructor
to participate in the dual credit program. If the local secondary instructor did not
choose to participate in the program, students were not eligible to participate;
3. Because the study relied on self-reports by participants in the sample, it was
vulnerable to participant bias;
4. The researchers assisted in developing the dual credit program and have published an
overview of the project as a poster session which may bias the study; however, the
researchers had the goal of providing factual and objective information for program
April 20-23, 2011
5
evaluation;
5. The information from this study will be provided to the College of Agricultural and
Life Sciences as an as an evaluative tool for directing future programming; and
6. Although the analyses indicated a positive relationship, some objectives had a small
number of completed responses.
Delimitations
Delimitations were defined as the restrictions that researchers impose in order to narrow the
scope of a study (Charles, 1998). For the purposes of this study, the delimitations were
identified as:
1. The population of the study was delimited to the 133 students who participated in the
initial year (2008-2009) of the Dual Credit program from the University of Idaho
College of Agricultural and Life Sciences; and
2. The study data were delimited to participant responses via the web-based survey.
Instrument
The instrument was developed by the researchers to target the research objectives presented.
The instrument was administered on-line using SurveyMonkey®. The following question types
were included:
a. Selection of only one option from a provided list: 7 questions;
a. 2 questions allowing an explanation;
b. Selection of multiple options from a provided list: 3 questions;
c. Likert-type scale – 6 ratings from Very Important to Not Important: 2 questions;
a. 1 question rating 10 Individuals;
b. 1 question rating 3 time frames of success;
d. Likert-type scale – 4 ratings from Large Influence to No Influence: 1 question;
a. 7 choices;
e. Yes/No question with explanation: 1 question; and
f. Open Ended: 1 question.
The individuals providing permission forms were invited to respond to the on-line survey on a
weekly basis from March to May, 2010 and a thank you note was sent to all respondents on May
9, 2010 (Cox & Cox, 2008).
The online format of the instrument also addressed the following principles: 1) introduced the
survey with a welcome screen; 2) provided a personal identification number or limited access
site to ensure only people in the sample had access to the survey; 3) chose the first question as
one interesting to the respondents, that was easily answered, and fully visible on the computer
screen; 4) presented each question in a format that was familiar and similar to a paper and pencil
instrument; 5) restrained use of color so the figure or ground consistency and reliability were
maintained, navigational flow was unimpeded, and measurement properties of the questions
were maintained; 6) avoided differences in visual appearance that resulted from computer
configuration, browsers, screen displays, and wrap-around text; 7) provided specific instructions
on how to take the necessary computer action to respond to questionnaire items; 8) used drop
down boxes sparingly; 9) did not require respondents to provide an answer to each question
before being allowed to answer subsequent ones; 10) constructed questionnaires to scroll from
April 20-23, 2011
6
question to question; 11) used graphical symbols or words that conveyed where the respondent
was in the completion process; and 12) exercised restraint in use of question structures that have
known measurement problems on paper (Dillman, 2007).
Validity and Reliability
“Measurement supplies the numbers we use in quantitative analyses” (Muijs, 2008, p. 64) and it
was necessary to ensure that the measurements taken from a survey through an identified
instrument measure what we wanted to measure. Muijs identified validity as the “single most
important aspect of the design of any measurement instrument” (p. 66). The necessity of
reporting quality findings lie in collecting quality data from a “good” instrument (Cox & Cox,
2008) which was defined as an instrument which must: a) address the intended content and
b) elicit accurate information. The researchers selected a panel of nine experts from the fields of
agricultural education, education, educational leadership, and research development to review
the survey instrument. The panel of experts gave input to the researchers regarding the content
and layout of the instrument which was incorporated into the final survey instrument.
Reliability referred to “the extent to which test scores are free of measurement error” (Muijs,
2008, p. 72). Repeated measurement and internal consistency were the main forms of reliability
(Muijs, 2008). The panel of experts agreed that no peer group for the participants existed and
pilot study from the participant pool was too limiting. A test-retest method had the potential to
provide a substantial crossover effect as well. Therefore, the entire study became a post-hoc
reliability study. Internal consistency was established by conducting a Cronbach’s Coefficient
Alpha test. The Cronbach’s Alpha test was calculated on the three questions within the
instrument questions which employed a Likert type scale to assess any outliers and two of those
questions were analyzed within this paper. The calculated Cronbach’s Alpha for overarching
question 3 which assessed the level of influence of nine individuals regarding participant
participation in the Dual Credit Program via a Likert type scale was 0.833. The Cronbach’s
Alpha for survey question 13 assessing perceived program impact on post secondary success
(assessing three aspects of success) was .971. Both values exceeded the established minimum
internal consistency value of 0.70 and indicated a good internal consistency for the survey
instrument. The additional Likert-type scale (question 16 assessing seven discrete factors
influencing participant decisions to enroll at the University of Idaho) exhibited a Cronbach’s
Alpha of 0.902.
Non-Response Threat and Generalizability
A total of 53 students of a population of 133 completed the survey for a response rate of
39.85 %. All 53 respondents were used in the data analysis. Non-response error can be a threat
to the external validity of a study anytime the response rate is below 100 %. To account for nonresponse, early and late responders were compared for statistical differences (Lindner, Murphy,
& Briers, 2001). Late responders were defined as the later 50 % of the respondents (Lindner, et
al., 2001). The 0.05 level of significance was established a priori when comparing early and late
responders as well as comparing the sample to the demographics of the total population.
Respondents’ home high school size was compared to that of the total population as well:
χ2 = 0.99. Gender was also compared between the total population and the respondents:
χ2 = 0.88. Neither of these significance values exceeded the minimum significance of 0.05
identified a priori.
April 20-23, 2011
7
Based on the Chi-Square values calculated comparing early responders and late responders, the
non-response error has been addressed and the threat to external validity has been minimized
(Lindner, et al., 2001). The results of the study will be generalizable to the target population
based on the minimal difference between early and late responders and no statistically significant
demographic difference between the total population and final sample.
Findings
Analysis of Dual Credit Program Participants – Total Population
Demographic data provided by the state of Idaho show 10,737 students [7,197 males (67 %) and
3,540 females (33 %)] enrolled in secondary agricultural education programs in the 2008-2009
school year (Ag Facts, 2008). Approximately 1.2 % of the total agricultural education student
population in Idaho participated in the Dual Credit Program.
The dual credit program courses were developed to align with state curriculum pathways in
Animal Systems (AVS 105 – Survey of the Science of Livestock Production and Management),
Plant Systems (PLSC 100 – Survey of Plant and Soil Sciences), and Agribusiness Systems
(AGEC 105 – Survey of Agribusiness) which would lead students in education through high
school and college to career placement. Agricultural education courses were also offered
(AGED 140: Intro to Organizational and Personal Leadership Development, AGED 158:
Introduction to Supervised Agricultural Experience Programs; AGED 159: Introduction to the
FFA; and AGED 160: Survey of the Expectations and Responsibilities of Teaching High School
Agriculture). Nationally, an agricultural education pathway has not been implemented in
Agriculture and Natural Resource Programs. The National FFA Organization, Supervised
Agricultural Experience Programs, and overall agricultural education were all identified as
integral components of a quality agriculture and natural resources program (Ag Facts, 2008).
Agricultural education courses offered through the Dual Credit Program were analyzed
separately as a fourth pathway. Although only 133 students enrolled in the program, total
student enrollment indicated 156 because students could enroll in multiple courses. Agribusiness
systems enrolled 15.8% (n = 21) of participants (non-duplicated), agricultural education courses
encompassed 58.6% (n = 78), animal systems included 8.3% (n = 11) of participants, and plant
systems enrolled 34.6% (n = 46) of program participants. Participants earned a total of 307
credits: agribusiness systems 10.4% (n = 32), animal systems 10.7% (n = 33), and plant systems
45% (n = 138). Agricultural education included 29% (n = 89) of the total credits earned.
In 2008-2009, students enrolled in the dual credit program from 33 of the 97 (34 %) agriculture
and natural resource programs statewide. The Idaho High School Activities Association
(IHSAA) Division 1AI Schools (100-159 students) enrolled 55 students (35.2 %) in the program,
the highest student enrollment from a high school classification. Division 1AI students earned
the most credits (111 credits, 35.2 %) as well.
Survey Results
The findings were grouped based on specific aspects of the primary research objective:
determine factors influencing high school student participation in the identified dual credit
program. Each of the specific aspects of the research objective were addressed.
April 20-23, 2011
8
a. Determine the perceived impact of the specifically studied dual credit program on
post secondary success of participants.
The one open-ended question asked the respondents to indicate what impact they perceived the
Dual Credit Program would have on post secondary success. Based on the responses, the
researchers grouped similar responses into 10 categories. The respondents indicated multiple
factors as impacting their post secondary success as a result of the dual credit program. The top
two response categories from the respondents were “providing head start on college credits”
(n = 33, 44.0 %) and “providing college experience to students” (n = 11, 14.7 %). Two
categories tied for third (n = 7, 9.3 %) including “saving money” and “course content.” The ten
categories and 75 responses identified an expected even distribution of 7.5 responses per
category, p= 0.000 significance. The Chi-Square significance indicated that the difference
among the responses was a significant difference and not the result of error.
b. Ascertain the frequency of individuals identified as providing information to program
participants.
Respondents were allowed to select multiple individuals who had provided information
regarding the dual credit program. However, a significant number of respondents (χ2 = 165.39,
0.01 level of significance, n = 50, 51 %) of the respondents indicated their secondary agriculture
teacher provided information regarding the Dual Credit Program. The second most selected
individual respondents indicated for providing program information was a friend (n = 10, 10 %).
Subsequently, respondents were asked to select from the same list of individuals, the single most
important source of information regarding the dual credit program. A significant majority of the
respondents (n = 43, 81.1 %, χ2 = 267.38, 0.01 level of significance) indicated that the secondary
agriculture teacher was the single most important source of information for respondents
regarding the Dual Credit Program. None of the respondents selected parents, high school
administrators, Internet site, other high school instructors, or other sources as their primary
information source.
c. Describe the participant enrollment in dual credit program pathways available.
The respondents were asked to identify each of the dual credit courses in which they had
enrolled, allowing for multiple responses (n = 73). Students enrolled in a minimum of one and a
maximum of six courses in the Dual Credit Program. The responses were then grouped by
pathway (Animal Systems, Plant Systems, Agribusiness Systems, and Agricultural Education)
Agricultural Education Pathway had significantly higher enrollment than the other pathways
(χ2 = 28.09, 0.01 level of significance, n = 36, 49 %), Plant Systems enrolled 20 (27 %), Animal
Systems enrolled 10 students (14 %), and the Agribusiness Systems Pathway had the lowest
enrollment overall (n = 7, 10 %).
d. Describe the perceived impact the participation in the dual credit program had on
participants.
Respondents were asked to rate the level of influence the Dual Credit Program had on their high
school and potential college and career success. Friedman’s Mean Rank test was utilized to
analyze the rank of participant responses within the Likert-type scale (Siegel, 1956). The
Friedman ranks indicated success after high school had the highest rank (1.85), college success
second (1.95), and career success third (2.20). Wilcoxon Signed Ranks Test comparison z-score
April 20-23, 2011
9
and 2-tailed significance for difference among each pair were calculated. The 0.05 significance
level was set a priori. The negative ranks yielded a significant difference in Pair 2 – College
Success and Career Success (0.012). The identified difference between success after high school
and college success, although visible, was not significant.
e. Ascertain the correlation between gender of dual credit program participants and
above identified aspects of the primary research objective.
Gender of the respondents was not statistically significantly correlated with any aspect of the
research objective (Table 1).
Table 1
Correlation of Gender to Specific Aspects of Research Objective
Specific Aspect of Research Objective
Pearson’s r
Two-Tailed Significance
Individuals who provided primary program
information to respondents
0.185
0.184
Differences in pathway enrollment
0.073
0.573
Program impact on success after high school
0.119
0.412
Program impact on college success
0.105
0.468
Program impact on career success
0.089
0.538
f. Ascertain the correlation between the secondary school size attended by dual credit
program participants and above identified aspects of the primary research objective.
The high schools were categorized according to the IHSAA General Classification and
Alignments. The classifications for 2008-2010 were used since the 2008-2009 school year being
studied falls within the classification timeline. HSAA General Classifications categorize high
schools by enrollment (IHSAA, 2010) and were as follows: 1A Division II, 99 students and
fewer; 1A Division I, 100-159 students; 2A, 160 – 319 students; 3A, 320 - 639 students; 4A, 640
– 1279 students; and 5A, 1280 students or higher. Size of the respondents’ home high school
was not statistically significantly correlated to any aspects of the research objective (Table 2).
Table 2
Correlation of Home High School Size to Specific Aspects of Research Objective
Specific Aspect of Research Objective
Pearson’s r
Two-Tailed Significance
Individuals who provided primary program
information to respondents
-0.137
0.328
Differences in pathway enrollment
0.035
0.766
Program impact on success after high school
0.031
0.828
Program impact on college success
0.086
0.552
Program impact on career success
0.025
0.865
Respondents were overall positive about the Dual Credit Program (93.2 %). Respondents
appeared to have had a generally positive experience in the Dual Credit Program. The general
April 20-23, 2011
10
tone of the comments provided by the respondents can be epitomized by the following statement:
“I strongly encourage high school students to participate in the Dual Credit Program, it’s a great
way to get ahead of the game and the classes start to add up and in some cases you can graduate
early because of this wonderful program!”
A majority of respondents gathered information about the Dual Credit Program from their local
agriculture instructor. The largest portion of respondents identified the secondary agriculture
teacher as the most important individual providing information to the student, which supported
support providing timely, quality program information to the local agriculture instructor.
The agricultural education pathway had significantly higher enrollment than other pathways;
however four courses were included in this pathway, whereas two courses were included in Plant
Systems, and one course each in Animal and Agribusiness Systems.
Participants identified success after high school as the largest impact of the Dual Credit Program,
followed by college success, and career success. The respondents indicated that the Dual Credit
program would have a more significant effect on college success than career success.
Neither gender nor respondent home high school size had significant relationships to the other
factors addressed in the study.
The findings of this study support the previous conclusions reached by Hoffman, Vargas, and
Santos (2009) indicating advantages of quality dual credit programs such as to provide realistic
information to high school students about the knowledge and skill needed in higher education,
decrease higher education cost by decreasing time and cost and create a reciprocal feedback loop
between secondary and post secondary education institutions.
Smith (2007) concluded that dual credit programs were to be considered an asset to the
educational process and a variety of outcomes were identified as being available for secondary
students participating in dual credit programs: The opportunity to enroll in college-level work
while still in high school (Andrews, 2004) and opportunity to earn up to one semester of college
credit prior to or immediately following high school graduation (Andrews, 2004; Kruegar, 2006)
were two primary advantages identified nationally for the implementation of dual credit
programs. This study supported both of these conclusions with a maximum of 6 credits earned
by participants through the CALS Dual Credit Program.
The respondents in this study identified success after high school as the highest ranking benefit
of the CALS Dual Credit Program, and participants ranked the dual credit program as having a
significantly higher impact on college success than career success. The participants in this study
supported the conclusions that return on investment for college and the benefit of attending
college were perceived benefits of participating in the Dual Credit program. However, cost
savings and the cost of attending the providing institution appeared to be less important.
This study focused on respondent perceptions on factors influencing participation in the CALS
Dual Credit Program, impact on post secondary success, the individuals providing information to
students about the program, enrollment in program pathways, the impact on participants and the
April 20-23, 2011
11
correlation between gender and high school size on responses. The information from this study
may also be useful to other institutions in developing similar programs and maintaining existing
programs nationwide.
Local secondary instructors are a vital aspect to successful recruitment and participation of
secondary students in dual credit programs and should be included in the development,
implementation, and maintenance of dual credit programs. The large percentage of respondents
who received information from the local high school agriculture teacher indicated the need to
provide timely, quality information regarding the dual credit program to secondary agriculture
programs; perhaps this is also an indication that school counselors and parents need to be
provided with additional information regarding the Dual Credit Program to assist students in
making informed decisions. The local teacher was identified as a significant influence in the
decisions of program participants regarding post secondary enrollment as well as program
participation. In all questions, the secondary agriculture instructor was identified as the highest
influencer as well as the individual providing the most information to participants. The
continuous feedback loop among secondary and post secondary educational professionals
(Kruegar, 2006) also lends support for utilizing constructivist leadership theory in developing
and maintaining reciprocal relationships among students, university faculty, and secondary
teachers in the educational setting (Lambert, et al., 1995); as well as, the practice of maintaining
and expanding the annual meeting between secondary and university faculty regarding program
content and direction.
Dual credit programs should start with curriculum relevant to both secondary and post secondary
programs and be expanded to meet the needs of students. Approximately 1.2 % of the total
enrollment of agricultural education students in the state enrolled in the program in the first year
representing 33 out of 97 programs (34 %). The program has potential to expand to a larger
population. The number of secondary agriculture programs participating should be expanded in
a cooperative effort between the College of Agricultural and Life Sciences and the state
agriculture teachers’ association. Expansion of the program should be considered based on
curriculum area and secondary student enrollment and interest statewide. Because the Power,
Structural and Technical Systems (PSTS) Pathway was identified as a fourth most common
pathway for secondary agriculture and natural resource programs with the state (Ag Facts, 2008;
Heikkila, Patten, & Wells, 2008), PSTS should be considered for the next pathway for dual
credit course development. Expanding Dual Credit offerings at the land-grant university will
provide the opportunity to develop and maintain a pipeline for the institution (Wilensky, 2007).
The pipeline or pathway concept ("The 16 career clusters," 2010; Bragg, 2007; Hoffman, Vargas,
& Santos, 2009; Touchstone, 2008) provided a course of study which allowed students to see
relationships not only among people but also among curriculums from the freshman level in high
school through the completion of a Baccalaureate degree.
Consistent information should be provided among stakeholders (students, teachers, parents,
school administrators and counselors) to maintain quality, rigor, and effectiveness of dual credit
programs. Because a majority of the students identified the local high school agriculture teacher
as the primary source of information regarding the Dual Credit Program, the established
communication system among the secondary and post secondary institutions becomes
increasingly valuable. The providing institution should continue to provide consistent, relevant,
April 20-23, 2011
12
and timely information regarding the program to the secondary agriculture programs.
Conversely, the dual credit program should facilitate communication from the secondary
instructors to the leadership of the program to enhance the content, rigor, and effectiveness of the
program courses. Additional information should be provided to parents and schools to assist
students in decision making as well. The continued relationship building and communication
feedback between stakeholders allows for the constructivist leadership (Lambert, et al., 1995)
direction of the Dual Credit Program. Faculty from the providing institution should take
advantage of opportunities such as FFA State Leadership Convention and FFA State Career
Development Events to further interact with students to establish and build additional
relationships to support recruitment efforts.
Recommendations for Further Research
Based on the results of this study, additional research seems indicated in the following areas:
1. Further research (and perhaps replication of this study) is indicated, as the sample size
and percentage of the total dual credit program student population, may limit
applicability of the results of this study. The final sample accounted for only 39.8% of
the population. However, the strong general directionality of the summative response
patterns does indicate that the results of this study may indeed be similar in studies that
garner final higher response rates.
2. Additional follow-up studies of Dual Credit Programs designed to assess perceived
impact on enrollment and post secondary success of participants are indicated in order to
assess and monitor the success level of current programs and areas of strengths and
weaknesses over time.
3. Longitudinal studies of Dual Credit Program participants will help clarify and further
define the relationship between program participation and post secondary education and
student success at that level.
4. Longitudinal studies of Dual Credit Programs and program participants will be required
to determine long-term impact (advantages and viability and impact) of the implemented
programs on the higher educational institutions offering dual credit programs.
5. Continued examination of this program might render valuable information regarding the
dual credit program partnerships between specific colleges and disciplines and K-12 dual
credit programs, and how those high school programs may provide valuable and high
quality instruction and course credit toward graduation in specialized programs,
curriculums, and colleges, considering increasing math and science graduation
requirements being implemented in Idaho.
Summary
Overall, this research may assist in identifying important variables in the creation and
implementation of successful Dual Credit Programs in areas of study related to Colleges of
Agricultural and Life Sciences. Universities nationwide may be able to utilize the results of
related studies to benefit and strengthen existing dual credit programs. The involvement of the
local secondary agriculture instructor may be a key to student recruitment and participation in a
dual credit program. The purposeful development, design, collaboration, and implementation of
the program evaluated in this research, certainly seem to indicate a definite positive directionality
toward the collaborative development of dual credit programs, especially in specialized
curriculum areas/colleges. The benefits of dual enrollment (and the improved transition between
April 20-23, 2011
secondary and higher education) may become the pathway to the evolution of new models of
education that improve that transition and usher in new and better institutional models of
education that meet the needs of today and the future.
April 20-23, 2011
13
14
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Muijs, D. (2008). Doing quantitative research in education with SPSS. Los Angeles, CA: Sage.
Osborne, E. W. E. (n.d.). National research agenda agricultural education and communication
2007-2010. Retrieved from
http://www.aaaeonline.org/files/researchagenda_shortlores.pdf
Proctor, R. W., & Capaldi, E. J. (2006). Why science matters. Maldin, MA: Blackwell.
Siegel, S. (1956). Nonparametric statistics for the behavioral sciences. New York, NY:
McGraw-Hill Book Company.
Smith, D. (2007). Why expand dual credit programs? Community College Journal of Research
and Practice, 31(371-387).
Touchstone, A. J. L. (2008). Agriculture programs of study. Boise, ID: Idaho Division of
Professional Technical Education Retrieved from
http://www.pte.idaho.gov/Clusters/ClustersPOSAg.htm
Waits, T., Setzer, J. C., Lewis, L., & Greene, B. (2005). Dual credit and exam-based courses in
U.S. public high schools: 2002-03. Washington, D. C.: National Center for Education
Statistics.
Wilensky, R. (2007). High schools have got it bad for higher ed - and that ain't good. Phi Delta
Kappan(December 2007), 248-259.
April 20-23, 2011
April 20-23, 2011
16
Social Comparison Theory as a Lens to View Job Satisfaction and Burnout
Tracy Kitchel
Associate Professor
University of Missouri
Rebecca Lawver
Assistant Professor
Amy Smith
Assistant Professor
South Dakota State
University
Anna Ball
Associate Professor
University of Missouri
Travis Park
Assistant Professor
Cornell University
Shane Robinson
Assistant Professor
Oklahoma State
University
Ashley Schell
Former Graduate Assistant
University of Kentucky
Abstract
Understanding the psychology around job satisfaction, stress, and burnout, as they are
situated within the agricultural education culture, brings ultimate bearing on the future of the
profession. The theoretical lens for studying this psychological phenomenon in agricultural
education lies the theory of Social Comparison, because of the multiple avenues in which
agriculture teachers can interact, and thus compare themselves to others. The impact of the
social comparison process on one’s self is most directly to affect emotions (Smith, 2000). Such
emotional developments can be linked to the teacher’s job satisfaction and be linked to
dimensions of burnout. This study sought to determine if relationships existed between social
comparison and job satisfaction and between social comparison and teacher burnout in
agriculture teachers across six states. Teachers tended to engage in upward assimilative (UA)
comparisons leading to inspiration emotional outcomes the most. In addition, teachers were
relatively satisfied with their jobs. According to the Maslach Burnout Inventory for Educators
(MBI-E) were experience low levels of burnout in relation to personal accomplishment (PA) and
depersonalization (DE), but did experience moderate levels of burnout in relation to emotional
exhaustion (EE). Seven moderate relationships were found between dimensions of social
comparison and either burnout and/or job satisfaction.
Introduction
Teaching is a demanding occupation with expectations for teachers to meet state and
national standards, and honor deadlines in an effort to increase student learning (Strauss, 2002).
Teaching agriculture is exponentially more demanding given that the roles of an agriculture
teacher are multi-faceted, and the workload extends well beyond a typical teacher work-week
(Torres, Lambert, & Tummons, 2009). One important research and professional development
imperative in agricultural education has been the retention and development of school-based
agricultural educators who are committed to and adept in managing a unique compilation of
work-place demands (Mundt and Connors, 1999; Myers, Dyer and Washburn, 2005). Thus,
understanding the psychology around job satisfaction, stress, and burnout, as they are situated
within the agricultural education culture, brings ultimate bearing on the future of the profession.
Job Satisfaction
First, the future of a highly qualified group of professionals hinges on the level of job
satisfaction in the profession. Job satisfaction is a variable that has been widely studied in social
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April 20-23, 2011
science research. Specifically, it has been studied in conjunction with qualities such as
“productivity, performance, absenteeism, and job turnover” (Jewell, Beavers III, Malpiedi, &
Flowers, 1990, p. 52). Although numerous scales for measuring job satisfaction exist, one of the
most used in agricultural education research is the Brayfield-Rothe (1951) job satisfaction
instrument, as modified by Warner (1973). Researchers have used this instrument to study
factors related to agricultural education faculty at higher education institutions (Bowen &
Radhakrishna, 1991), college of agriculture faculty (Castillo & Cano, 2004), secondary
agricultural education instructors (Bruening & Hoover, 1991; Cano & Miller, 1992a; Cano, &
Miller, 1992b; Castillo & Cano, 1999; Castillo, Conklin, & Cano, 1999; Newcomb, Betts, &
Cano, 1986; Walker, Garton, & Kitchel, 2004), agricultural education graduates (Garton &
Robinson, 2006; Robinson & Garton, 2008), and supervisors of agricultural employees (Barrick,
1989).
Job satisfaction is described best as an individual’s feelings about his or her job. It is
dependent on the individual’s attitudes and levels of motivation toward performing tasks
associated with their job (Gilmer & Deci, 1977). Martin (2002) stated that a satisfied worker is
more effective and productive than an unsatisfied worker. Robinson and Garton (2006) stated
that assessing levels of job satisfaction is important because satisfied workers tend to be more
committed to their careers overall. Job satisfaction can subsequently impact career longevity and
tenure. Gregg and Wadsworth, as cited in Morley (2001), found that job tenure has decreased
from seven to four years. In fact, Boverie and Kroth (2000) concluded that employees are “job
hopping” more now than ever before. Therefore, it is important that research be conducted to
determine how satisfied individuals are with their chosen career field in an attempt to understand
their potential job tenure better.
Burnout
The level of stress associated with a job is an important emotional precursor to job
satisfaction, and as widely documented in the literature, agriculture teachers experience
challenges that form particular job stressors (Greiman, Walker, & Birkenholz, 2005; Walker,
Garton & Kitchel, 2004). Agriculture teachers are particularly susceptible to stress and its
ultimate outcome, burnout, as they often work long hours, usually beyond a 40-hour work week
(Straquadine, 1990; Vaughn, 1990). Symptoms of stress in teachers can include anxiety and
frustration, impaired performance, and damaged interpersonal relationships at work and at home
(Kyriacou, 2001). Troman and Woods (2001) noted that teachers who experience stress over
long periods of time may experience what is known as burnout. Matheny, Gfoerer, and Harris
(2000) described burnout as a loss of idealism and enthusiasm for work. A more extensive
description of burnout provided by LeCompte and Dworkin (1991) stated burnout is an extreme
type of role-specific alienation with a focus on feelings of meaninglessness, especially as this
applies to an individual’s ability to reach students successfully.
Related, Maslach, Jackson, and Leiter (1996) highlighted three important reasons to study
teacher burnout, the ultimate consequence of teacher stress. First, teaching is an extremely
visible profession. Second, teachers are expected to teach beyond academics into moral
development to correct social problems. Third, meeting diverse needs and expectations of
students requires numerous human and financial resources. Finally, the image of teachers is
eroding as policymakers convolute the situation with conflicting answers to the ills of education.
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To that end, Maslach et al. developed an educator version of their burnout inventory that
measures dimensions of emotional exhaustion, depersonalization, and personal accomplishment.
Social Comparison Theory
In tying together the concepts of satisfaction and burnout with the unique culture that is
agricultural education, the theory of Social Comparison provides explanation to certain
emotional outcomes that may bring about either positive satisfaction or negative satisfaction and
stress that could lead to burnout. In his theory of Social Comparison, Festinger (1954)
hypothesized that people have the desire to evaluate their own opinions and abilities in relation
to the opinions and abilities of others. “For example, a person’s evaluation of his ability to write
poetry will depend to a large extent on the opinions which others have of his ability to write
poetry” (Festinger, 1954, p. 118). Consequently, Wood, Taylor, and Lichtman (1985) found that
those who make frequent social comparisons should be happy if they believe they are better off
than the people they compare themselves with.
Social comparison exists in today’s society and examples of social comparison in the
workforce, particularly in education, have been demonstrated; however, there is little research
regarding social comparison among agricultural educators. The basis for studying social
comparison in agricultural education programs is the model that embodies three intra-curricular
components that are equally important: FFA, SAE and class/laboratory (National FFA
Organization, 2003). In particular, there are multiple avenues in which agriculture teachers can
interact, and thereby compare themselves to others. This could occur through competition in
FFA via conferences, conventions, professional meetings, and district/regional teacher meetings.
A mathematics teacher, for example, may not have the quantity of mechanism to meet and
interact with fellow mathematics teachers at neighboring schools or schools in the state as do
agriculture teachers. Further, agriculture teachers at local, regional, state, and even national
meetings, competitions, and conferences have ample opportunities to socially compare
themselves to other agriculture teachers to potentially positive and negative outcomes for the
individual teacher. This presents a unique context in which to study this phenomenon of social
comparison, and what social comparison might mean for retaining and developing agriculture
teachers who are more satisfied in their professions, less stressed, and less likely to experience
the phenomenon of burnout.
Much research has been conducted in the area of social comparison, and the theory has
evolved over time. Wills (1981) proposed that social comparison intertwined with selfevaluation, and served to affect individual’s self-esteem, and functioned as a coping mechanism.
Aspinwall and Taylor (1983) found that social comparison is used to manage negative affect,
while Collins (1996) found that social comparison is used to affiliate upward. Taylor and Lobel
(1989) found that when under stress, people are more likely to compare themselves to those who
are in worse situations. One of the most current concepts of social comparison is that of Buunk
and Gibbons (1999) who found that social comparison is whenever individuals compare their
own characteristics to others. This comparison can occur on many levels.
Social comparisons can be directional; people can make upward comparison and
downward comparisons. Individuals engage in upward comparison when they compare
themselves to peers who they perceive to be performing in a more competent or adequate way.
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April 20-23, 2011
On the other hand, individuals engage in downward comparison with peers when they compare
themselves to those who they perceive to be performing in a less competent or inadequate way
(Carmona et al., 2006). Both types of social comparison are frequently used.
In addition, social comparisons can be contextual set as either assimilative or contrastive
in nature (Smith, 2000). Social judgments are strongly based upon some context and the values
or standards associated with said context (Wedell, 1994). According to Wedell (1994), “contrast
refers to the displacement of judgments away from the values of contextual stimuli. . .
assimilation, on the other hand, refers to the displacement of judgment toward the contextual
standard” (p. 1007).
Social comparisons can have emotional consequences. Buunk and Ybema (1997) found
that, when used as a reference point, people feel relieved when they see that others are doing
“worse,” and feel envious when they see that others are doing “better” than them. Also, when
comparing upward, individuals may be inspired because they feel like they have become the
comparison target. In contrast, when comparing downward, individuals may lose their good
feeling about themselves because they fear ending up in a similar situation (Buunk & Ybema,
2004). Smith (2000) summarized the interactions in Figure 1. The smaller outer boxes, as a set
of three in a corner formation, indicate the emotional outcomes of social comparison based on 1)
whether or not the comparison is upward or downward, 2) whether the emotions are assimilative
or contrastive, and 3) whether or not the outcome is desirable for self or others.
Figure 1. Social Comparison-based Emotions (Smith, 2000, p. 176)
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Examples of Social Comparison in Work and Educational Settings
Sweeney and McFarlin (2004) found that income satisfaction can be a factor of social
comparison. In the United States, people were less satisfied with their income when compared to
people with similar education and jobs in other countries (Sweeney & McFarlin, 2004). Japan
and Russia tended to exhibit the same characteristics as the United States, while the remaining
countries varied in their social comparison effects (Sweeney & McFarlin, 2004).
Social comparison also plays a role in an individual’s relationship satisfaction. Titus
(1980) found that many people make comparisons about their own personal relationships when
talking with friends. Surra and Milardo (1991) supported this notion by suggesting that people
engage in social comparisons with their friends, generally, in order to evaluate their beliefs about
their close relationships, the suitability of their partner, and their feelings and experiences in
those relationships. In their study, Buunk and Ybema (2004) found that in spite of high levels of
marital satisfaction, people will regard another’s marriage as better than their own in an upward
comparison.
Teachers also frequently compare themselves to other teachers in their building, in their
district, and across the state. Carmona et al. (2006) researched if burnout among teachers is
related to social comparison. In their study, the researchers found that positively interpreted
upward comparisons were related to lower burnout levels, while negatively interpreted
downward comparisons were related to higher burnout levels. When teachers compare
themselves with others who they feel are performing at a higher level, and they feel that this is a
positive experience, they will be less likely to experience job burnout. When teachers compare
themselves with others who they feel are performing at a lower level, and they feel that this was
a negative experience, they are more likely to experience job burnout because they realized they
were not performing at a high level.
The impact of the social comparison process on one’s self is most directly to affect
emotions (Smith, 2000). Van Yperen, Brenninkmeijer, and Buunk (2006) sought to determine if
practicing teachers responded differently to upward and downward social comparison in terms of
affect and the intent to work harder. The researchers found that an individual’s effortperformance expectancy explained the different responses to upward and downward social
comparison information. They argued that practicing teachers respond differently to upward and
downward social comparison information. Their findings showed that the personal belief of
doing a job well, if effort is made, was correlated to positive affect after upward social
comparison. This demonstrated that the stronger the individual’s effort-performance expectancy
the more upward social comparisons may occur.
Satisfaction and Burnout as Results of Social Comparison
As described earlier, emotional outcomes could ensue based upon how social comparison
plays out. If social comparison in agricultural education exists, and emotion outcomes are
produced, what is the result of that process? In determining a way to operationalize this
phenomenon, job satisfaction and teacher burnout should be considered. If positive and/or
negative results of social comparison are present, it would be important to identify those results
so that teacher educators, state staff, and teachers can address it through the implementation
and/or redesign of programs. It is important to assess the culture of the agricultural education
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profession through the lens of social comparison; such a lens may provide rationale for the
positive and/or negative results that is the unique context of the agricultural education profession.
Purpose and Methods
The purpose of this descriptive-relational study was to determine if relationships existed
between social comparison and job satisfaction and between social comparison and teacher
burnout. The following objectives were developed to guide the study:
1.
2.
3.
4.
5.
Determine the degree of social comparison in which agriculture teachers engage
Determine the level of job satisfaction of agriculture teachers.
Determine the degree of teacher burnout experienced by agriculture teachers.
Determine the relationship between social comparison and job satisfaction.
Determine the relationship between social comparison and teacher burnout.
The population of the study was high school agriculture teachers from six states
(Kentucky, Missouri, New York, North Dakota, Oklahoma, Utah). For each respective state, a
frame was identified, which provided contact information for all current high school agriculture
teachers. Each frame was then scrutinized for errors, omissions, and duplicates to address
potential frame error and to ensure accuracy.
A random sample was selected from the frames of two states with agriculture teacher
populations larger than 300 (Missouri and Oklahoma). For the remaining states, all teachers
were invited to participate in the study because the difference between the size of those states’
population and the size required for a representative sample was small. In addition, the
geographic spread of the states involved was considered a beneficial factor. One state was
located in the southern part of the United States (Kentucky), one from the east (New York), two
from the Midwest (Missouri and North Dakota), one from the southwest (Oklahoma) and another
from the west (Utah). As such, readers are cautioned on inferring the results beyond the scope of
this study as findings can only be generalized to the high school agriculture teachers from the six
states.
An online instrument was utilized to collect data and was distributed via email using
Hosted Survey™, a web-hosted software application. The instrument consisted of three key
sections, as well as a demographic section. Specifically, the instrument sought to obtain
information regarding social comparison, job satisfaction, and burnout of high school agriculture
teachers. Further descriptions of each section are described further.
Social Comparison
To measure social comparison and the dimensions of upward/downward and
contrastive/assimilative, the Social Comparison Style Questionnaire (SCSQ) instrument
developed by Leach et al. (n.d.) was utilized. There were four constructs to this part of the
instrument: downward assimilation (DA), downward contrast (DC), upward contrast (UC), and
upward assimilation (UA). DA was aligned with the emotion “worry;” an example of an item
was “learning that another agriculture teacher is worse off than I suggests that my situation might
get worse in the future as well.” UA was aligned with the emotion “inspiration.” An example
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April 20-23, 2011
item in this construct was “agriculture teachers who are more successful than I excite and/or
challenge me to do better”. DC was aligned with the emotion “gratitude.” An example item in
this construct was “seeing agriculture teachers with difficult working conditions really helps me
appreciate my own life.” Whereas UC was aligned with “inferiority.” An example item in this
construct was “I often feel angry that I'm not as competent of an agriculture teacher as others.”
Because of the context-specific nature of social comparison, items were revised from the original
Leach et al. instrument to provide focus to a person comparing him/herself to other agricultural
education teachers and/or their program. There were seven questions from UC, five questions
from UA, four questions from DA, and three questions from DC.
A panel of experts reviewed the instrument for face and content validity. Further, the
instrument was pilot-tested using 19 agriculture teachers from a state not utilized in this study.
Calculations using Cronbach’s alpha indicated coefficients of .75 (DA), .76 (DC), .89 (UC), and
.91 (UA). As such, the instrument was deemed reliable (Nunnally, 1967).
Job Satisfaction
Castillo and Cano (2004) sought to determine if a one-item measure of job satisfaction
was as valid an instrument as opposed to a multi-item measure of job satisfaction. To accomplish
this objective, the authors “standardized and compared” (p. 71) the one-item instrument to the
multi-item instrument and found no differences existed in scores. As such, the researchers
concluded that a one-item instrument could adequately assess an individual’s level of job
satisfaction. Therefore, for the purpose of this research, job satisfaction was assessed by asking
teachers to respond on their level of agreement with the question, “How satisfied are you with
your job?”
Burnout
The Maslach’s Burnout Inventory for Educators (MBI-E) was utilized to measure
burnout. The MBI-E was selected because of its specific application to teachers and
measurement of multiple dimensions of burnout. In particular, the MBI-E measured three
burnout subscales including Emotional Exhaustion (EE), Depersonalization (DP), and Personal
Accomplishment (PA). According to the MBI manual, emotional exhaustion is described as “the
tired and fatigued feeling that develops as emotional energies are drained,” while
depersonalization refers to the act of portraying negative or indifferent attitudes towards ones’
students (p. 28). The third subscale measures personal accomplishment; this subscale may
indicate a teacher’s feelings regarding the contributions they are making to student growth and
achievement (Maslach, Jackson, & Leiter, 1996).
The only difference between the MBI-E and the standard MBI is the use of the term
“student,” rather than “recipient.” A total of 22 items comprise the commercially available
instrument, which has been assessed for validity and reliability. Two factor analysis studies,
conducted between 1981 and 1984 supported the use of three subscales (Gold, 1984; Iwanicki &
Schwab, 1981). With regard to reliability, Cronbach’s alpha reliability estimates ranging from
.72 to .90 were also reported by Iwanicki and Schwab (1981) and Gold (1984).
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Data Collection
Using features offered by HostedSurvey, a modified version of the Dillman (2007)
Tailored Design Method guided data collection. Typically, this method is utilized for mailed
instruments and includes five contacts (Dillman). However, because this instrument was
delivered via email, the contacts were slightly modified. Immediately prior to the first email
invitation, a key contact from each respective state sent a personalized message to the teachers
within that state. This was done to introduce the idea of the study to the teachers, prior to receipt
of the first email, in effort to increase the overall response rate. One day after this pre-notice was
sent, teachers received the first invitation to participate. Two additional contacts were made with
those teachers who had not completed the instrument; these were sent at one-week intervals. As a
result, 383 out of the invited 944 participated in the study, giving a 40.57% response rate.
Data Analysis
Objectives 1-3 were analyzed using means and standard deviations for the scaled items.
Objectives 4-5 were analyzed using the Pearson-product Moment Correlation. Because social
comparison was the variable of interest, the table was constructed around the four social
comparison constructs. Davis (1971) conventions were used to interpret correlation coefficients.
Findings
Objective 1 sought to determine the degree of social comparison in which agriculture
teachers engage. In terms of degree of social comparison, agriculture teachers mostly engage in
upward assimilation (M = 4.58; SD = 0.75), meaning as they compare themselves to someone
perceived as better, they engage in emotions relating to inspiration (Table 1). Next, agriculture
teachers engage in downward contrast (M = 3.94; SD = 0.92), meaning as they compare
themselves to someone perceived as worse off, they engage in emotions relating to gratitude.
Finally, agriculture teachers in this study engage in upward contrast (M = 2.42; SD = 0.95), and
downward assimilation (M = 2.12; SD = 0.84) social comparisons.
Objective 2 sought to determine the level of job satisfaction of agriculture teachers (Table
1). According to the single item, agriculture teachers seemed satisfied with their job (M = 6.04;
SD = 1.06). Objective 3 sought to determine the degree of teacher burnout experienced by
agriculture teachers. According to the MBI-E, agriculture teachers experience “low” levels of
burnout on the depersonalization construct (M = 6.92; SD = 5.79) and personal accomplishment
construct (M = 37.83; SD = 6.34). However, agriculture teachers experienced “moderate” levels
of burnout on the emotional exhaustion construct (M = 20.27; SD = 11.01).
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Table 1.
Descriptive Statistics for Social Comparison, Job Satisfaction and Burnout (n = 383)
Variable or Construct
Mean
Standard Deviation
Social Comparison Construct
Upward Assimilation (UA) “Inspiration” 1
4.58
0.75
1
Downward Contrast (DC) “Gratitude”
3.94
0.92
Upward Contrast (UC) “Inferiority” 1
2.42
0.95
1
Downward Assimilation (DA) “Worry”
2.12
0.84
Job Satisfaction 2
6.04
1.06
Teacher Burnout (MBI-E)
Emotional Exhaustion (EE) 3
20.27
11.01
Depersonalization (DP) 4
6.92
5.79
5
Personal Accomplishment (PA)
37.83
6.34
1
Based on a scale from 1 to 6, with 1 being “strongly disagree” and 6 being “strongly agree”
2
Based on a scale from 1 to 7, with 1 being “strong dissatisfied” and 7 being “strongly satisfied”
3
EE interpreted as high (27 or over), moderate (17-26) and low (0-16)
4
DP interpreted as high (14 or over), moderate (9-13) and low (0-8)
5
PA interpreted (in reverse as EE/DP) as low (37 or over), moderate (31-36) and high (0-30)
Objective 4 sought to determine the relationship between social comparison and job
satisfaction. Related, objective 5 was to determine the relationship between social comparison
and teacher burnout. Pearson-product correlation coefficients were calculated to determine these
relationships. Note that when interpreting the burnout construct of personal accomplishment,
higher mean scores indicated lower levels of burnout.
Table 2.
Correlation Coefficients for Social Comparison with Job Satisfaction and Teacher Burnout
Social Comparison Construct
Job Satis. (JS) Burnout: PA Burnout: EE Burnout: DP
Upward Contrast (UC)
-0.40
-0.29
0.44
0.40
Upward Assimilation (UA)
0.35
0.29
-0.17
-0.12
Downward Contrast (DC)
-0.37
-0.27
0.39
0.30
Downward Assimilation (DA)
0.16
0.16
-0.13
-0.05
The strongest relationships tended to exist on the upward contrast scale (Table 2). As
such, the more that agriculture teachers engage in comparisons of other, better agriculture
teachers, and when those comparisons lead to inferiority, the more their satisfaction decreases (r
= -0.40) and their burnout levels increase (rPA = -0.29; rEE = -0.44; rDP = -0.40). Using Davis’
(1971) conventions, the following combinations elicited moderate relationships: UC and EE (r =
0.44); UC and JS (r = -0.40); UC and DP (r = 0.40); DC and EE (r = 0.39); DC and JS (r = 0.37); UA and JS (r = 0.35); DC and DP (r = 0.30). Three combinations elicited low
relationships bordering moderate: UC and PA (r = -0.29); UA and PA (r = 0.29); DC and PA (r
= -0.27). All other relationships were clearly in the low to negligible relationship range.
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Discussion
While the study included a fairly large sample size representing six states in a variety of
regions across the country, the results should be interpreted with caution. The study is limited by
a 40% response rate, and not every state in the nation was represented. Thus, the findings should
not be generalized beyond the six states in the study. For research Objective 1 it was concluded
that agriculture teachers engaged mostly in the social comparison of upward assimilation. Thus,
the agriculture teachers in this study make upward comparisons of themselves to other teachers
and they admire, look up to, or are inspired by the accomplishments of those teachers and think
that they might be able to live up to similar accomplishments (Smith, 2000). This finding could
imply that agriculture teachers are in a positive emotional state as they compare themselves to
others. It would stand to reason that agriculture teachers engaging in upward assimilation as a
form of social comparison want positive outcomes for their colleagues and for themselves
through their admiration of other successful teachers and could be positively engaged by the
successes of others. This implication would be consistent with teacher research that suggested
that teachers who engage in upward social comparison believe that if they make the effort to do
their job well, that they will improve and grow in positive professional directions (Van Yperen,
Brenninkmeijer & Buunk, 2006). Further research is needed to investigate the influence of
social comparison on motivation, teaching self efficacy, and measures of teacher success in the
classroom.
It was further concluded that agriculture teachers in this study have feelings of downward
contrastive social comparison toward their colleagues. Thus, some teachers when comparing
themselves to others, look down upon others and experience feelings of pride or relief that they
are not like them or in situations like them (Smith, 2002). This finding implies that agriculture
teachers might scorn and have negative attitudes about their colleagues that they feel are not
doing as good of a job as themselves. The notion of agriculture teachers engaging in downward
contrastive emotions toward their colleagues poses interesting questions. Does the professional
culture in agricultural education create a situation where teachers wear their jobs as a badge of
honor and scorn others they feel are not performing to the same level?
Because comparisons are perception-based, each person’s comparison of “worse off”
(downward comparison) is different. Based upon this premise, “worse off” could merely be a
question of being different. Thus, does the professional culture allow for teachers who perform
the job in different ways, or do professionals scorn others who are different? The results of this
study certainly do not point social comparison in any cause-effect direction. Further research is
needed in social comparison regarding who teachers make social comparisons toward, specific
situations in which they compare themselves socially with others, and what teachers use as their
frames for upward (better off) and downward (worse off) comparisons.
It was further concluded in this study that agriculture teachers are satisfied with their job,
which is consistent with previous literature (Walker, Greiman, and Kitchel, 2004). This finding
could imply that the individuals who took the time to complete the questionnaire were likely
individuals who would be more satisfied with their job in the first place. While teachers are
generally satisfied, further research is needed to investigate the specific sources of their
satisfaction, conditions or factors of their jobs that are the most and least satisfying, and
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motivators and barriers for individuals who are the least satisfied with their jobs. It is also
recommended that professional development programs designed to recruit and retain agriculture
teachers utilize this finding as a means to communicate to the public that many teachers report
that they are satisfied with teaching agriculture.
It was further concluded that teachers are experiencing low levels of burnout as it pertains
to depersonalization and personal accomplishment; however teachers are experiencing moderate
levels of burnout as it pertains to emotional exhaustion. This finding could imply that while
teachers in this study might not be feeling alienated toward their profession or their ability to
perform well as teachers (LeCompte & Dworkin, 1991), they could be feeling the emotional
implications of a complex and multifaceted career. Further research is needed regarding the
specific sources of emotional exhaustion for agriculture teachers. Further research is also needed
regarding the specific factors that help combat emotional exhaustion in agriculture teachers.
Professional development programs for agriculture teachers should keep indicators of emotional
exhaustion in mind and design uplifting programs that emotionally empower teachers.
In regard to the relationship between social comparison and job satisfaction it was
concluded that the teachers who compared themselves to others and felt feelings of inferiority as
a result were less likely to experience feelings of satisfaction with their jobs. Further teachers
who compared themselves to others and felt inspired by others’ accomplishments were more
likely to experience feelings of satisfaction with their jobs. Finally, teachers who compared
themselves to others that they looked down upon with appreciation that they were not in that
same place were less likely to experience feelings of satisfaction with their jobs. Findings
regarding the relationships between social comparison and job satisfaction pose potentially
interesting implications. For example, the findings could imply that positive emotions of others
(social comparison) and positive outlook for the self (job satisfaction) vary together.
One question for further research and hence a limitation of correlational studies is that
from this study it cannot be determined which emotional outcome (if any) serves as the cause or
the precursor to the other. Do people who like their jobs tend to feel positive about others in a
profession or do feelings of connection and positivity within a profession lead to higher job
satisfaction? Further, it was concluded that negativity in terms of social comparison and job
satisfaction varied together as well. Again, further research is needed regarding the specific
causes of and precursors to the negative emotional outcomes of contrastive social comparison
and job dissatisfaction. Further research is needed regarding the social and emotional climate of
agricultural education as a profession. Do local and statewide teacher associations in agricultural
education foster a climate of sameness, and what effect does the climate have on teachers?
Professional development programs for agriculture teachers should take emotional concerns of
satisfaction, social comparison and burnout into consideration. Programs should be designed
with the less emotionally satisfied in mind.
Regarding social comparison and teacher burnout, it was concluded that teachers who
experienced upward assimilative emotions of social comparison felt more personal
accomplishment, less emotional exhaustion and fewer feelings of depersonalization. Further,
teachers who felt a sense of envy or depression when thinking about more successful colleagues
also felt fewer feelings of personal satisfaction, more feelings of emotional exhaustion and more
11
April 20-23, 2011
feelings of depersonalization toward their career. Finally, teachers who look down upon
colleagues they felt to be worse off with scorn also felt less personal satisfaction toward their
careers, more emotional exhaustion and more feelings of depersonalization toward their careers.
These findings are consistent with the Carmona, Buunk, Piero, Rodriguez, and Bravo (2006)
investigation of the relationships between social comparison and burnout. These findings again
point toward the notion of positivity and it’s potential implications. While it might be no
surprise those positive social feelings and positive outcomes (lack of burnout or greater
satisfaction) would increase together, again the question remains regarding causation. Are
people who naturally feel a particular way toward a profession drawn to that profession, more
successful in the profession, more positive about it, more satisfied, and less burned out?
Conversely, is as they say, “ignorance bliss”? Meaning, are those who are blissfully satisfied,
less burned out and happier with others socially? Regardless, further research is warranted
regarding both positive and negative emotions in agriculture teachers and the effects of teacher
affect on teacher success and ultimately student outcomes. Finally, teacher professional
development programs should be based upon this notion of positive psychology and emotional
outcomes and seek to foster feelings of positive emotions in teachers at all levels.
12
April 20-23, 2011
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Technical Curriculum Professional Development Needs of Missouri School-Based
Agriculture Teachers Based Upon Career Stage
Rob Terry, Jr., Oklahoma State University
Abstract
Professional development education for teachers is essential to improving teacher retention,
program continuity, and the preparation of fully qualified and highly motivated agricultural
educators at all career stages (Osborne, n.d.). This research investigated the self-assessed,
professional development needs of school-based agriculture teachers in Missouri, at all of
Huberman’s (1989) career stages, using the direct assessment method. A census of the
population was conducted with data collection administered at area agricultural education
teacher meetings and via an electronic questionnaire for those teachers who could not attend
those meetings. Results, regardless of teacher career stage, indicated that teachers have the
greatest in-service needs in the areas of agricultural mechanics technology, bio-technology,
animal science, and leadership development. To improve the technical competence of these
teachers, Missouri agricultural educators should receive professional development in-service
education in these areas. According to literature (Barrick, Ladewig, & Hedges, 1983; Birkenholz
& Harbstreit, 1987; Saucier, Schumacher, Funkenbusch, Terry, & Johnson, 2008; Saucier,
Tummons, Terry, & Schumacher, 2010), these professional development in-service education
programs should be delivered by Missouri agricultural teacher educators and state agricultural
education supervisory staff and offered during technical workshops and summer conferences.
In the early 1900’s, school-based agricultural education programs were primarily focused
on production agriculture with the ultimate goal of preparing students to return to the farm and
pursue a career in production agriculture (Leake, 1915). At the time, these programs consisted of
classroom lecture, recitation, and manual labor (Stimson as cited in Moore, 1988). As challenges
facing agricultural educators have changed over time (Layfield & Dobbins, 2002; Washburn &
Dyer, 2006; Saucier, Tummons, Terry, & Schumacher, 2010) so has in-service education
programming. Agricultural education programs have evolved from production oriented training
at their inception, to consumption based curriculum and courses that are offered today
(Washburn & Dyer, 2006). Modern teachers are expected to provide a positive learning
environment for students and ultimately prepare them for productive lives in a fast-paced world
(Layfield & Dobbins, 2002). Moreover, they are also encouraged to integrate science,
mathematics, engineering, and technology (STEM) curriculum into many of the agricultural
education courses that they teach (Washburn & Dyer, 2006). The constant evolution of
agricultural education programs and the addition of core subject content skills have required
many teachers to seek professional development opportunities to meet the demands of the
changing emphasis of their programs (Washburn & Dyer, 2006).
Functionally, the intention of professional development is to provide educators the
essential knowledge, skills and technical information required for them to effectively carry out
April 20-23, 2011
their professional duties and meet the demands of a changing educational environment (Barrick,
Ladewig, & Hedges, 1983; Birkenholz & Harbstreit, 1987; Nesbitt & Mundt, 1993; Washburn,
King, Garton & Harbstreit, 2001). Traditionally, professional development education for
agriculture teachers has been a duty of collegiate agricultural education programs and state
agricultural education supervisory staff (Barrick, et al.). The planning and implementation of
these professional development opportunities has generally been developed with little input from
educators in the field (Washburn, et al.) Historically, three key methods have been used by
teacher educators and state supervisory staff to determine the in-service needs of agriculture
educators: research (Layfield & Dobbins, 2000; Washburn, et al.), personal experiences (Barrick
et al.), and informal inquiry with current agricultural educators (Barrick et al.; Roberts & Dyer,
2004).
A critical factor in developing successful teachers is correctly identifying professional
development needs that are in the greatest demand (Layfield & Dobbins, 2002). By recognizing
the problems faced by agricultural educators, teacher education faculty and state agricultural
education supervisory staff can improve professional development programs to address the needs
of teachers (Mundt & Connors, 1999). Literature suggests that providers of continuing education
programs have experienced difficulties at times in identifying appropriate topics to include in
professional development programs (Washburn, et al., 2001). According to Birkenholz and
Harbstreit (1987), providers of professional development education should monitor the needs of
agriculture teachers over time and provide educational programs based upon their current needs.
Furthermore, Garton and Chung (1995) concluded that “the in-service needs of agriculture
teachers should be assessed and prioritized on a continual basis” (p. 78).
Consequently, Waters and Haskell (1989) suggested that current educators be included in
the process to identify contemporary professional development in-service needs of teachers.
They stated that “gathering data from potential clientele and actively involving them in the
process of identifying potential educational programs increases the likelihood of implementing
relevant educational programs; thus, increasing the likelihood of achieving appropriate
outcomes” (p. 26). Newcomb, McCracken, and Warmbrod (1993) agreed stating “individuals are
more motivated to learn when they are actively involved in planning learning activities” (p. 32).
In 2007, Park, Moore, and Rivera conducted a study of New York agricultural science educators
and found that teachers believed professional development was most meaningful to them when it
was personalized to their needs. Additionally, when teachers felt engaged, they set their own
learning expectations, became interested, and asserted themselves toward changing their teaching
practices. By understanding the major problems facing school-based agriculture teachers, teacher
educators and state supervisory staff can make improvements in the professional development inservice programs offered to today’s teachers (Washburn & Dyer, 2006).
The researchers utilized both Knowles’ (1980) Theory of Andragogy and the Teacher
Career Cycle Model (Huberman, 1989) as theoretical base(s) to guide this study. Knowles
Theory of Andragogy states that adults need to know why they need to learn something and
become more motivated to learn when they see the need to learn. The theory further states that
adults learn experientially, learn as problem solvers, and learn best when the topic is of
immediate value to them. Knowles’ stated that adults should be engaged in the planning of their
own learning experiences. Huberman’s Teacher Career Cycle Model (TCCM) illustrates the
April 20-23, 2011
interrelationships found among complex phenomena and provides a theory about the sequences
teachers may follow throughout their careers (see Figure 1). Within this model, teacher career
stage is divided into five phases: career entry- discovery and survival (1-3 years), stabilization
(4-6 years), experimentation/diversification (7-18 years), serenity (19-30 years), and
disengagement (31 years and beyond). To better understand teachers’ professional development
needs, teacher career stage was considered a significant variable in the planning process
(Layfield & Dobbins, 2002).
Teacher
Career
Stages
Themes/Phases
Stage 1
(1-3 years)
Career Entry:
Discovery and Survival
Stage 2
(4-6 years)
Stabilization
Stage 3
(7-18 years)
Experimentation
/ Diversification
Shock-taking/
Interrogations
Stage 4
(19-30 years)
Serenity
Conservatism
Stage 5
(31+ years)
Disengagement
(“serene” or “bitter”)
Figure 1. Illustration of the Teacher Career Cycle Model (Huberman, 1989).
According to Witkin (1984), no one model or conceptual framework for needs
assessment has been universally accepted. While empirical evidence has failed to prove one
method to be superior over another, many professional development studies have used the Borich
Needs Assessment Model (Borich, 1980) to determine the in-service needs of teachers (Garton &
Chung, 1995, Saucier, Terry, & Schumacher, 2009). Witkin (1984), however, stated that the
educational needs of a group could be better evaluated by using a variety of needs assessment
models. To measure the in-service needs of Missouri agriculture teachers, the researchers utilized
the direct assessment method to determine the self-perceived education needs of teachers
(Birkenholz & Harbstreit, 1987; Briers & Edwards, 1998). Due to the length of the instrument
and the limited amount of contact time researchers had with the population, use of the Borich
Needs Assessment Model (1980) was not feasible. Consequently, the researchers chose the direct
April 20-23, 2011
assessment method that allowed agricultural educators the opportunity to have a role in the
identification of future professional development topics.
Ten years have elapsed since the last comprehensive study of professional development
in-service needs of Missouri agricultural educators. In previous studies, researchers found that
Missouri agricultural educators had in-service needs in the following areas: developing
agribusiness management skills, electricity skills, training FFA contest teams, assisting students
with SOEP records, completing reports for local and state administrators, motivating students to
learn, developing an effective public relations program, preparing proficiency award
applications, use of computers, writing grant proposals, attracting quality students, biotechnology applications, and landscaping (Birkenholz & Harbstreit, 1987; Garton & Chung,
1996; King & Garton, 2000). Due to the length of time since those studies were conducted and
the continual need for research regarding the professional development in-service needs of
agricultural educators (Osborne, n.d.), an assessment of current professional development needs
of agriculture teachers was warranted based upon teacher career stage.
Purpose and Research Objectives
The purpose of this study was to identify the professional development needs of Missouri
agricultural educators, as related to technical agriculture teaching topics, and based upon teacher
career stage. The following research objectives were investigated to accomplish this purpose:
1. Describe the personal and professional characteristics (years of teaching experience, sex,
FFA membership, 4-H membership, and type of teacher certification) of school-based
agricultural educators in Missouri.
2. Describe the professional development needs of school-based agricultural educators in
Missouri, as related to technical agricultural curriculum topics, and based upon teacher
career stage.
Population
The population for this study was all school-based agricultural education teachers in
Missouri (N = 467). Subjects were identified from the 2008-2009 Missouri Agricultural
Education Directory (2008) and were confirmed by the agricultural education professional
development staff of the Missouri Department of Elementary and Secondary Education (J.
Tummons personal communication, September 1, 2008).
Methodology
The data collection instrument utilized for this study was adapted from the questionnaire
created by Garton and Chung (1995) . The instrument contained two sections. The first section
was composed of items describing competencies associated with teaching school-based
agricultural education. Those competencies were organized into five constructs: curriculum and
instruction, preparation of a career development event team, program management and planning,
April 20-23, 2011
student and teacher development, and technical agricultural curriculum topics. Competencies
were identified through a review of relevant literature and from input of a panel of experts. The
panel of experts was composed of three university faculty members with expertise in agricultural
education, four agricultural education graduate students with prior school-based agricultural
education teaching experience, a professional development specialist from the agricultural
education division of the Missouri Department of Elementary and Secondary Education, and a
university faculty member with expertise in research methods and data collection instrument
design. Response choices for each item were the following five-point, anchored, summated
rating scale: 0 = no need, 1 = little need, 2 = some need, 3 = much need, and 4 = highest need.
The second section of the instrument was designed to collect data related to selected personal
and professional demographic characteristics of the respondents. Characteristics investigated
were: years of teaching experience, sex, FFA membership, 4-H membership, and type of teacher
certification.
The panel of experts described above was also utilized to determine the face and content
validity of the instrument. After implementation of suggestions provided by the panel, the
instrument was judged to be valid. A pilot test was conducted to determine the reliability of the
instrument. The pilot test group was composed of 20 experienced school-based agricultural
education teachers from Missouri who served as mentors in a mentor/inductee program for first
and second year agricultural education teachers. Due to their participation in the pilot study,
these teachers were excluded from the census. Cronbach’s alpha (Cronbach, 1951) was used to
measure the reliability of the instrument using data collected from the pilot group. Cronbach’s
alpha was calculated for each construct in the study yielding the following results: Curriculum
and Instruction (.94), Preparation of a Career Development Event Team (.90), Program
Management and Planning (.95), Student and Teacher Development (.90), and Technical
Agricultural Curriculum Topics (.87). These alpha levels were deemed to be acceptable
indicators of instrument reliability (Nunnally & Burnstein, 1994).
Concluding the establishment of validity and reliability, the instrument was administered
to the population. A census was conducted of all Missouri agricultural educators, excluding the
pilot group. The questionnaire was administered at each of the 16 area agricultural education
teacher meetings. This stage of data collection resulted in 310 acceptably completed
questionnaires, yielding a 69.35% response rate. A second round of data collection was
conducted to gather data from teachers who did not attend one of the area meetings. An online
instrument, using the same competencies as the paper instrument, was utilized in the second
round of data collection and yielded responses from an additional 16.33% (n = 73) of the
population. The response rate resulting from the two stages of data collection was 85.68% (n =
383). Responses from both stages of data collection were only extrapolated to the respondents of
the study and not to the overall population of teachers; therefore, no issues of non-response error
were addressed for this study.
Data Analysis
Data relative to the research objectives were analyzed utilizing SPSS 18.0 and Microsoft
Excel®. Descriptive statistics were calculated for all professional development competencies and
demographic characteristics. For research objective one, the mean, standard deviation, and range
were calculated for the demographic characteristic years of teaching experience. Frequency and
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percentage were calculated for the remaining demographic characteristics. For research objective
two, means, standard deviations, and overall rank of in-service need were calculated for each
professional development competency. The following anchors were used to describe the means
for professional development in-service need: no need = 0.00 – 0.50; little need = 0.51 – 1.50;
some need = 1.51 – 2.50; much need = 2.51 – 3.50; highest need = 3.51 – 4.00. Additionally, a
grand mean was calculated for each career stage using the mean from each competency.
Findings
Findings Associated with Research Objective 1
The first objective was to describe selected personal and professional characteristics of
the teachers. The average years of teaching experience for Missouri agricultural educators who
participated in this study was slightly more than 10 (M = 10.14; SD = 8.29), with a range of
experience from 1 year to 38 years. More than 70% (n = 272; 71.01%) of the agricultural
educators who participated in this study were male. A total of 339 (88.50%) Missouri
agricultural educators reported that they had been a member of the National FFA Organization.
In addition, 222 (58.00%) of the respondents reported that they had been a 4-H member as a
youth. Nearly 9 out of 10 (n = 340; 88.80%) of Missouri agricultural educators reported that they
had a traditional agriculture teacher certification while only 7.80% (n = 30) hold an alternative
agriculture teacher certification. The remaining 30 (3.40%) respondents did not designate the
type of certification that they possess.
Findings Associated with Research Objective 2
The construct Technical Agricultural Curriculum Topics was operationally defined as
technical agricultural curriculum that is taught by teachers in Missouri agricultural education
courses. As displayed in Table 1, the grand mean for this construct was 2.22, meaning teachers
perceived some need for professional development education in this area. Global Positioning
Systems (GPS) ranked as the highest professional development education need in the construct
(M = 2.54; SD = 1.04) followed by Bio-Fuels (M = 2.53; SD = 1.02) and Bio-Technology (M =
2.51; SD = 0.99). Teachers (n = 383) rated 3 of the 26 items in this group to be topics for which
they have much need for professional development. The competency Companion Animal Care
ranked as the lowest professional development education need in this construct (M = 1.91; SD =
1.10).
As displayed in Table 1, school-based agriculture teachers (n = 90) who self-reported to
be in Career Stage 1(1-3 years), indicated that their greatest need for professional development
education was in the competency of Agricultural Structures (M = 2.69; SD = 1.00). This area was
followed by Agricultural Mechanics Project Construction (M = 2.63; SD = 1.04) and Bio-Fuels
(M = 2.54; SD = 0.96). Teachers rated 4 of the 26 competencies in this construct to be topics for
which they have much need for professional development. Companion Animal Care (M = 1.83;
SD = 0.96) ranked as the competency with the lowest professional development need in this
construct for teachers in Career Stage 1. The grand mean for this construct was 2.30, meaning
teachers had some need for in-service education for the technical agricultural curriculum topics
found within the construct.
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Teachers (n = 78) in Career Stage 2 (4-6 years), reported that the competencies Bio-Fuels
(M = 2.64; SD = 1.09) and Bio-Technology (M = 2.64; SD = 1.01), ranked as their highest
professional development education needs. This area was followed by Veterinarian Assistant
Training (M = 2.44; SD = 1.14). Only 3 of the 26 competencies in this construct were ranked by
teachers as being of much need in terms of professional development education. The competency
with the least need for professional development was Companion Animal Care (M = 1.83; SD =
1.14). For teachers in Career Stage 2, the grand mean for this construct was 2.25, denoting that
teachers had some need for in-service education for the technical agricultural curriculum topics
found within the construct. (see Table 1)
Teachers with 7 to 18 years of experience (Career Stage 3) had some need for in-service
education for the technical agricultural curriculum topics found within the construct (M = 2.20.)
The top three competencies, with the highest need for professional development, were: Global
Positioning Systems (M = 2.58; SD = 1.06), Bio-Fuels (M = 2.50; SD = 1.02), and BioTechnology (M = 2.47; SD = 0.99). Four competencies in this construct were identified by
teachers of being of much need for professional development education. Companion Animal
Care (M = 1.84; SD = 1.16) ranked as the lowest competency for professional development
within this construct. (see Table 1)
For the 58 teachers who reported their teaching tenure to be within the fourth career stage
(19-30 years), the grand mean for the construct of Technical Agricultural Curriculum Topics was
2.25, or teachers indicated that they had some need for education in this construct. These teachers
indicated that Global Positioning Systems (M = 2.79; SD = 0.93) was the competency in which
they had the highest need for professional development. This area was followed by the
competencies Bio-Technology (M = 2.64; SD = 0.85) and Renewable Energy Sources (M = 2.60;
SD = 0.86). The competency with the least need for professional development education was
Cold Metal Work (M = 1.81; SD = 0.95). Overall, 5 of the 26 competencies were determined to
be of much need for professional development education (see Table 1).
For the teachers (n = 5) in Career Stage 5 (31 + years), the competency Animal Nutrition
(M = 3.00; SD = 0.71) was the highest professional development education need. This area was
followed by the competencies: Animal Reproduction (M = 2.80; SD = 1.10), Bio-Technology (M
= 2.80; SD = 1.10), Hot Metal Work (M = 2.80; SD = 0.84), and Leadership Development (M =
2.80; SD = 0.84). The competency with the least need for professional development was Floral
Design (M = 1.40; SD = 1.14). Within this construct, 11 of the 26 competencies were reported by
teachers as having much need for professional development education. For teachers in career
stage 5, the grand mean for this construct was 2.32, or teachers indicated that they had some need
for education in this construct. These data are displayed in Table 1.
April 20-23, 2011
Table 1
Teachers’ Self-Perceived Need for In-Service for Competencies Associated with Technical Agricultural Curriculum Topics
Based Upon Career Stage (n = 383)
Teacher Career Stage
Competency
1
2
3
4
5
Overall
n = 90
n = 78
n = 132
n = 58
n=5
n = 383
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
Global Positioning
Systems (GPS)
2.52
1.03
2.40
1.07
2.58
1.06
2.79
0.93
2.60
0.55
2.54
1.04
Bio-Fuels
2.54
0.96
2.64
1.09
2.50
1.02
2.59
0.80
2.60
1.52
2.53
1.02
Bio-Technology
2.42
1.05
2.64
1.01
2.47
0.99
2.64
0.85
2.80
1.10
2.51
0.99
Agricultural
structures
2.69
1.00
2.28
1.17
2.35
1.16
2.36
0.89
2.20
1.10
2.40
1.09
Agricultural
mechanics project
construction
2.63
1.04
2.33
1.11
2.31
1.15
2.33
0.98
2.60
0.55
2.36
1.10
Animal
reproduction
2.45
0.87
2.33
1.05
2.27
1.12
2.34
0.85
2.80
1.10
2.32
1.01
Veterinarian
assistant training
2.26
1.11
2.44
1.14
2.17
1.18
2.57
1.03
1.80
1.30
2.30
1.14
Leadership
development
2.33
1.03
2.35
1.02
2.26
0.99
2.34
0.97
2.80
0.84
2.29
1.00
Genetic engineering
2.17
1.00
2.42
1.06
2.31
1.11
2.36
0.99
2.60
0.55
2.29
1.05
(Continued)
April 20-23, 2011
Competency
1
2
3
4
5
Overall
n = 90
n = 78
n = 132
n = 58
n=5
n = 383
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
Natural resource
management
2.33
0.95
2.28
0.92
2.23
1.08
2.41
0.94
2.40
0.55
2.27
1.00
Landscaping
2.35
0.98
2.42
0.95
2.21
1.02
2.22
1.09
2.20
1.10
2.27
1.01
Renewable energy
sources
2.20
1.01
2.23
1.17
2.25
1.11
2.60
0.86
2.40
0.89
2.27
1.07
Food science
2.18
1.02
2.31
1.13
2.31
1.15
2.31
0.88
2.00
0.71
2.25
1.08
Greenhouse
management
2.35
1.05
2.32
1.10
2.20
1.08
2.19
1.07
2.00
0.71
2.24
1.06
Electricity
2.40
1.07
2.24
1.03
2.19
1.09
2.12
0.80
2.40
1.14
2.23
1.04
Small engine
technology
2.34
1.13
2.29
1.22
2.11
1.13
2.19
.092
2.00
0.71
2.22
1.12
Alternative animal
production
2.38
1.01
2.17
0.93
2.11
1.08
2.22
0.94
2.20
1.10
2.19
1.01
Tractor restoration
2.22
1.27
2.09
1.16
2.18
1.31
2.09
1.17
2.60
1.14
2.15
1.25
Agricultural
communications
2.18
0.94
2.29
0.92
2.10
0.94
2.14
0.81
2.20
0.84
2.14
0.93
Record keeping
skills
2.38
0.91
2.19
1.05
2.07
1.10
1.97
0.96
2.40
1.14
2.14
1.03
Animal nutrition
2.30
0.82
2.04
0.78
2.08
1.04
2.14
0.76
3.00
0.71
2.13
0.90
(Continued)
April 20-23, 2011
Competency
1
2
3
4
5
Overall
n = 90
n = 78
n = 132
n = 58
n=5
n = 383
M
SD
M
SD
M
SD
M
SD
M
SD
M
SD
Show animals
2.26
1.12
2.19
1.15
2.11
1.11
1.84
0.91
2.20
0.84
2.11
1.10
Hot metal work
2.38
1.07
1.94
1.10
2.15
1.18
1.97
1.06
2.80
0.84
2.11
1.13
Cold metal work
2.30
1.15
1.99
1.08
2.20
1.22
1.81
0.95
2.60
0.89
2.09
1.15
Floral design
2.02
0.99
2.18
1.11
2.01
1.11
2.00
0.98
1.40
1.14
2.02
1.07
Plumbing
2.07
1.05
2.00
1.09
2.02
1.19
2.02
0.78
2.00
0.71
2.01
1.08
Tissue culture
1.87
1.09
2.14
1.18
1.94
1.17
2.10
1.20
1.80
1.48
1.99
1.15
Companion animal
care
1.83
0.96
1.83
1.14
1.84
1.16
2.29
1.03
1.60
1.14
1.91
1.10
Grand mean
2.30
2.25
2.20
2.25
2.32
2.22
Note. Scale: no need = 0.00 – 0.50; little need = 0.51 – 1.50; some need = 1.51 – 2.50; much need = 2.51 – 3.50; highest
need = 3.51 – 4.00. Teacher career stage: career entry- discovery and survival (1-3 years), stabilization (4-6 years),
experimentation/diversification (7-18 years), serenity (19-30 years), and disengagement (31 years and beyond) (Huberman,
1989). Teachers who failed to report years of teaching experience (n =19).
April 20-23, 2011
Research Objective 1
The typical school-based agricultural educator in Missouri is a male with 10 years of
teaching experience. As a youth, he was a member of the National FFA Organization and 4-H. In
addition, he holds a traditional teacher certification in agricultural education. Factors such as
career stage, location, length of time, time of year, cost, graduate school credit, and use of
distance education technology (synchronous and asynchronous) should be considered in
developing professional development programs for agriculture teachers.
Research Objective 2
School-based agricultural educators in Missouri have professional development needs
related to teaching many areas of technical agriculture. Two of the three greatest in-service needs
of early career teachers, or teachers in Career Stage 1 (1-3 years), are related to curriculum areas
associated with traditional agricultural mechanics: Agricultural Structures and Agricultural
Mechanics Project Construction. The areas of greatest in-service need for teachers in Career
Stages 2 (4-6 years), 3, (7-18 years), and 4 (19-30 years) are in the areas of emerging agricultural
mechanics technology such as: Global Positioning Systems, Bio-Fuels, and Bio-Technology.
Interestingly enough, veteran teachers in Career Stage 5 (31 + years) have the greatest need for
in-service in traditional curriculum areas such as: Animal Nutrition, Animal Reproduction, Hot
Metal Work, and Leadership Development. However, teachers in Career Stage 5 also identified
emerging technology, such as Bio-Fuels, as an in-service need too.
According to Osborne (n.d., p. 20), a research based professional development program
will result in “an abundance of fully qualified and highly motivated agricultural educators at all
levels.” Based upon the conclusions of this research, several implications must be considered.
Interestingly, many of the top professional development needs identified in this study by teachers
of all career stages relate to school-based agricultural mechanics curriculum. However, many of
these technical curriculum areas (Global Positioning Systems, Bio-Fuels, and Bio-Technology)
did not exist when many teachers were enrolled in pre-service agricultural education programs.
Based upon the results of this study, many questions concerning the professional development of
teachers go unanswered and may be grounds for future research. Why do teachers feel such a
need for professional development related to agricultural mechanics? Are existing teachers being
pro-active in seeking professional development, as indicated by the results of this study, towards
curriculum areas that did not exist at the inception of their teaching career? Has this specific field
of the agricultural education curriculum shifted to areas in which teachers have no previous
experience or has the increase in technology in agricultural mechanics surpassed the existing
knowledge level of teachers? Furthermore, the question must be asked of pre-service programs in
Missouri as to the level in which they adequately prepare beginning teachers in the technical area
of agricultural mechanics? Moreover, have state leaders failed to provide in-service programs,
related to developing agricultural mechanics technology, for existing teachers? Many of these
questions and others should be asked of pre-service and in-service agricultural education
programs in the U.S.
April 20-23, 2011
Teacher educators have identified agricultural mechanics as a vital part of secondary
agricultural programs (Burris, Robinson, & Terry, 2005). Research also supports the point that
many agriculture teachers, at all career levels, are in need of continuing professional
development in the curriculum area of agricultural mechanics (Fletcher & Miller, 1995; McKim,
Saucier, & Reynolds, 2010; Saucier et al., 2008; Saucier et al., 2009; Swan, 1992).
Acknowledging the aforementioned research and the results of this study, what agricultural
mechanics courses are required of pre-service teachers within U.S. agricultural teacher education
programs? Are these pre-service teachers instructed by agricultural education faculty or are these
academic responsibilities bestowed to faculty members/ graduate students in other departments?
Are pre-service teachers adequately prepared to instruct school-based agricultural education
courses? These questions and others must be answered if pre-service agricultural education
programs are to progress and prepare “fully qualified and highly motivated agricultural
educators” (Osborne, n.d., p. 20).
According to the National Research Agenda for Agricultural Education and
Communication a “well designed professional development experiences, based upon teacher
career stage, may improve teacher retention and program continuity” (Osborne, p. 20).
Additionally, literature suggests that “practicing teachers must have continuing access to high
quality professional development programs” (2007, p. 20). Acknowledging the work of Osborne
and others (Barrick et al., 1983; Birkenholz & Harbstreit, 1987; Garton & Chung, 1996; Saucier
et al., 2008; Saucier et al., 2009; Saucier et al., 2010), it is recommended that studies similar to
this one be conducted periodically to ensure the continuing education needs of teachers are met.
Results of this study confirm recommendations by Huberman (1989), as well as Layfield and
Dobbins (2002), that teacher career stage should also be considered when developing
professional development opportunities.
Recognizing that knowledge and technology related to agriculture constantly evolve,
coupled with the fact that the average years of experience of agriculture teachers in this
population is only 10 years, the researchers recommend that a comprehensive assessment of
professional development be conducted every five years. State agricultural education leaders and
teacher educators should use such information and plan meaningful and timely professional
development opportunities for agriculture teachers. Various demographics of the population,
namely career stage, location within the state, length of time, time of year, cost, the availability
of graduate school credit, and the use of distance education technology (synchronous and
asynchronous), should be considered when planning and offering professional development
education.
Furthermore, there is a national directive to integrate core academic subjects into career
and technology education (National Science Board, 2010) to better prepare the future national
workforce. Many of the technical agricultural curriculum topics that emerged as areas of greatest
in-service need, are curriculum areas that lend themselves to STEM integration. Consequently,
planners and providers of professional development education should offer more workshops and
in-service opportunities to teachers that focus on the integration of science, technology,
engineering, and mathematics (STEM) into agricultural education courses.
April 20-23, 2011
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April 20-23, 2011
Technology Acceptance Related to Second Life™, Social Networking,
Twitter™, and Content Management Systems:
Are Agricultural Students Ready, Willing, and Able?
Theresa Pesl Murphrey, Texas A&M University
Tracy A. Rutherford, Texas A&M University
David Doerfert, Texas Tech University
Leslie D. Edgar, University of Arkansas
Abstract
Technology has the potential to improve education but only if it is applied with purpose and
consideration of the audience. Understanding technology’s role in education goes beyond the
comparison of tools; there is a need to better understand student acceptance of technology so
that appropriate educational scaffolding and support can be provided. The absence of
technology acceptance can become a barrier to the adoption and successful implementation and
use of new technologies. Described in the study is agricultural students’ acceptance and
readiness to use Second Life™, social networking, Twitter™, and content management systems
as educational tools. The theoretical framework was based on technology acceptance,
specifically the Unified Theory of Acceptance and Use of Technology (Venkatesh, Morris, Davis,
& Davis, 2003). A total of 716 completed surveys were analyzed. Findings revealed that
students perceive each of the technologies studied (Second Life, social networking, Twitter, and
content management systems) as unique entities that vary in regard to acceptance. Students
overwhelmingly accept content management systems as a useful educational technology while
Second Life, Twitter, and social networks (while familiar) are not as accepted.
Introduction
The use of technology to improve education and the teaching/learning process has been studied
in the context of agricultural education from multiple perspectives. Extensive research has been
conducted in regard to the use of technology by teachers (Kotrlik & Redmann, 2009; Murphrey,
Miller, & Roberts, 2009), the delivery of courses online (Alston & English, 2007), and the use of
distance education for courses and programs (Roberts & Dyer, 2005a). In addition, specific
aspects of technology use has been studied including the use of the Internet as a source of
information (Rhodes, Irani, Telg, & Meyers, 2008), Web 2.0 technologies (Rhodes, Friedel, &
Irani, 2008), and the use of illustrated web lectures (Roberts & Dyer, 2005b). In the study
conducted by Rhodes, Irani, et al. (2008), the authors call for continued research on this topic in
order to enable effective use of the technologies.
Second Life™, social networking, Twitter™, and content management systems have each
received various degrees of attention in the literature. Only limited research has been conducted
on the use of Second Life as an educational tool. O’Connor (2010) examined graduate level
teacher-education courses that utilized Second Life and reported “social and collaborative gains
[are] possible” (p. 213). Hargis (2008) stressed the importance of understanding “how we learn”
(p. 62) in order to take advantage of the opportunities of using tools such as Second Life in
education. The author compares informal learning to that which can be experienced in Second
April 20-23, 2011
Life. In many ways – Second Life does away with racial and cultural issues – while at the same
time offering new opportunities for exposure and experience without leaving the comfort of
one’s home.
Rhodes, Irani, et al. (2008) reported high use of social networking (85.2% on Facebook) and
high use of content management systems by agricultural students. The authors suggest that the
high use of social networking sites indicates a potential opportunity for instruction using these
tools. In regard to Twitter (a tool that allows immediate communication to individuals and
groups via 140-character text messages, known as microblogging), Shultz and Doerfert (2010)
reported that students were familiar with Twitter but did not use it on a regular basis. Reaction
to the use of Twitter for educational purposes was not strong in the study. Content management
systems have been studied in the context of distance education. Roberts and Dyer (2005a)
reported that “content management software was the technology used most to deliver courses”
(p. 70) in distance education settings across agricultural education.
The National Research Agenda for Agricultural Education and Communication (Osborne, 2007)
calls for continued research on “nonformal educational delivery systems,” “enhancing [ing] the
effectiveness of agricultural and life science faculty,” and “enhance[ing] program delivery
models for agricultural education” (p. 3). Understanding technology’s role in education goes
beyond the comparison of tools; there is a need to better understand student levels of knowledge
and technology savviness so that appropriate educational scaffolding and support can be
provided. The absence of technology acceptance can become a barrier to the adoption and
successful implementation and use of new technologies; thus, there is a need to study the
readiness and willingness of students to use new technologies for instructional purposes. This
study sought to add to our knowledge base by documenting technology acceptance related to
emerging technologies including Second Life, social networking, Twitter, and content
management systems.
The theoretical framework for this study is based on technology acceptance. Technology
acceptance relates to predictions of technology use and factors that can impact use (Lederer,
Maupin, Sena, & Zhuang, 2000). There have been multiple models used to study technology
acceptance. Venkatesh, Morris, Davis and Davis (2003) devised “core determinants of intention
and usage” (p. 425) related to technology acceptance and identified this theory as the Unified
Theory of Acceptance and Use of Technology (UTAUT). The UTAUT is based upon a review
and rigorous evaluation and analysis of constructs presented in eight different models including
Roger’s Innovation Diffusion Theory. The eight models include: the Theory of Reasoned
Action, the Technology Acceptance Model (TAM), the Motivational Model, the Theory of
Planned Behavior (TPB), Combined TAM and TPB, the Model of PC Utilization, the Innovation
Diffusion Theory, and the Social Cognitive Theory. The UTAUT theory takes into account a
total of 32 constructs that were identified across the models and resulted in constructs that could
determine “user acceptance and usage behavior” (Venkatesh et al., 2002, p. 447).
The UTAUT constructs determined to affect intention and use included performance expectancy,
effort expectancy, social influence, facilitating conditions, and behavioral intention to use the
April 20-23, 2011
system. Performance expectancy was defined as “the degree to which an individual believes that
using the system will help him or her to attain gains” (Venkatesh et al., 2003, p. 447). Concepts
such as “perceived usefulness,” “relative advantage,” “extrinsic motivation,” and “outcome
expectations” are included in this construct (p. 447). Effort expectancy was defined as “the
degree of ease associated with the use of the system” (p. 450). Concepts of “ease of use” and
“complexity” are included in this construct (p. 450). Social influence was defined as “the degree
to which an individual perceives that important others believe he or she should use the new
system” (p. 451). This construct included aspects of “social factors,” “image,” and “social
influence” (p. 451). Facilitating conditions was defined as “the degree to which an individual
believes that an organizational and technical infrastructure exists to support use of the system”
(p. 453). Behavioral intention was described as one’s intention to use a technology. Venkatesh
et al. (2003) identified three constructs that were not direct determinants and therefore were not
addressed in this study. These constructs included “self-efficacy, anxiety, and attitude” (p. 461).
The purpose of this descriptive study was to describe agricultural undergraduate and graduate
students’ current level of technology readiness related to Second Life, social networking,
Twitter, and content management systems. The following objectives guided the study: (a)
determine the demographic background of responding students enrolled in a College of
Agriculture, (b) determine technology awareness of responding students based on selfassessment, and (c) document technology acceptance based on the UTAUT Model focused on
Second Life, social networking, Twitter, and content management systems.
Survey research methodology was implemented to achieve the objectives of the study. The
instrument included three sections: (a) background/demographic information, (b) technology
awareness, and (c) technology acceptance. Each section was developed based on a review of the
literature. The instrument was reviewed for face validity and clarity by a team of five faculty
members. The instrument was pilot tested with a group of 11 students enrolled in a course not
included in the population. Minor grammar and layout modifications were made following
review. Open-ended questions were included on the instrument but were not included as part of
this manuscript due to page limitations.
Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the foundation for
assessing technology acceptance, response items for 19 Likert-type questions were created with a
7-point Likert-type scale ranging from “Strongly Disagree” to “Strongly Agree” for each of the
four technologies (Second Life, social networking, Twitter, content management systems) under
study. According to Venkatesh et al. (2003), in regard to the UTAUT, “all internal consistency
reliabilities (ICRs) were greater than .70” (p. 457). Thus, the instrument was determined to be
reliable. Table 1 reveals the alpha coefficients ranging from .612 to .939 for the dependent
variables based on the administration of the instrument for this study. According to Nunnally
(1967), a modest reliability of .60 or .50 is sufficient during early stages of research. All
constructs revealed acceptable reliability levels except for “facilitating conditions.” Close
April 20-23, 2011
inspection of the construct revealed two statements that were not reliable and were thus removed
from the construct, resulting in 17 statements that were analyzed as part of this study.
Table 1
Reliabilities by Construct and Technology (17 statements; 5 constructs) (N = 716)
Construct
Content
Mgmt.
System
Second
Life
Twitter
Social
Networks
Performance Expectancy (4)
.930
.913
.859
.853
Effort Expectancy (4)
.906
.904
.846
.865
Social Influence (4)
.797
.753
.612*
.722
Facilitating Conditions (2)
.661*
.726
.864
.900
Behavior Intentions to Use (3)
.888
.927
.939
.904
.897
.901
.862
.919
Overall Reliability (17)
*Note: Due to the low reliability, caution should be used in interpreting findings.
The population for this study consisted of all students enrolled in eight courses at Texas A&M
University during the Fall 2010 semester. Courses included both undergraduate and graduate
students. Course rosters were compared and duplicate students were removed from the complete
listing of potential respondents. Students enrolled in more than one of the courses under study
only completed the instrument once and thus were only counted once in regard to response rate.
A total of 793 unique undergraduate and 45 unique graduate students were enrolled in the
courses under study. Surveys were administered during normal class hours in face-to-face
settings using a paper instrument.
Data were scanned into the PASW Statistics computer program. Instruments with excessive
missing data were removed from the study. A total of 716 completed surveys were analyzed
yielding a response rate of 85% for undergraduates (671 of 793) and 90% for graduate students
(45 of 50). As shared by Lindner, Murphy, and Briers (2001), any response rate less than 100%
has the potential for a “threat to external validity” (p. 51); however, the authors indicate that a
response rate at the 85% response level does not require additional procedures. Given that the
response rate for this study fell within the parameters noted, no additional procedures were
performed. Data analysis included the calculation of frequencies, percentages, means and
standard deviations.
Findings
a. Demographic background of responding agricultural students.
Demographic details of responding students are presented in Table 2. The responding sample
included 716 students who were predominately undergraduates (93.7%) and female (66.3%).
April 20-23, 2011
Nearly half of the respondents reported that they had completed online courses, while more than
30% of these reported the completion of two or more courses. In regard to age, more than half of
the respondents (57.3%) were 19 years old or younger, while only 8.1% were 23 years or older.
Table 2
Demographic Information for Responding Students (N = 716)
Demographic
Characteristic
Category
Age* (n = 715)
19 & younger
410
57.3
20-22
247
34.5
23 & older
58
8.1
Female
475
66.3
Male
241
33.7
Undergraduate
671
93.7
Graduate
45
6.3
0
363
51.3
1 course
128
18.1
2 or more courses
216
30.6
Gender
Classification
Online Courses Completed
(n = 707)
f
%
*Note: Students were asked to write their age as of Sept. 1, 2010. Data were coded to create age
categories based on responses.
b. Technology awareness of students based on self-assessment.
Technology awareness was assessed by asking students to report their use and comfort with
technology. Tables 3 and 4 provide detailed responses. All students reported the use of e-mail
and a majority of students reported the use of social networks (97.5%), Internet access (99.7%),
and YouTube (92.4%). Blogs, Twitter and virtual worlds were reported to not be used by a high
percentage of students.
The majority of students described themselves to be either intermediate (67.3%) or advanced
(22.1%) computer users (See Table 4). More than 90% of students reported being comfortable
with new computer technology and 87.4% reported having broadband Internet access at home.
Less than 2% of the students reported dial up or no Internet access. Eighty-five percent of the
students reported “consistently high” or “generally good” quality of Internet connection at home.
April 20-23, 2011
Table 3
Students’ Reporting of Internet-based Technology Use (N = 716)
No
Yes - Some
f
%
Yes – A Lot
f
%
f
%
E-mail
0
0.0
117
16.3
599
83.7
Internet access
2
0.3
96
13.4
618
86.3
Social networks (n = 714)
16
2.2
131
18.3
567
79.2
YouTube (n = 713)
51
7.1
462
64.5
200
27.9
Blogs (n = 709)
560
78.2
123
17.2
26
3.6
Twitter™ (n = 710)
605
84.5
80
11.2
25
3.5
Virtual worlds (n = 705)
664
92.7
36
5.1
5
0.7
Table 4
Students’ Reporting of Computer Technology Ability and Comfort
How would you classify yourself as a user
of computer technology? (n = 714)
f
%
Advanced
158
22.1
Intermediate
482
67.3
71
9.9
Non-User
3
0.4
No Response
2
0.3
Comfortable
437
61.0
Very Comfortable
217
30.3
Not Comfortable
56
7.8
6
0.8
Novice
How comfortable are you with using a
new computer technology (n = 710)
No Response
April 20-23, 2011
c. Technology acceptance of students based on the UTAUT Model.
Student responses to statements based on the UTAUT model for each of four technologies
(Second Life, social networking, Twitter, and content management systems) were unique for
each of the technologies. See Tables 5, 6, 7, and 8 for responses to each technology based on the
four constructs.
Second Life.
On a scale of 1 to 7 (with 7 indicating strong agreement), students indicated that Second Life was
a technology supported by their institution (Facilitating Condition M = 5.07, SD = 1.74), but not
a technology that would assist them in their education (Performance Expectancy M = 2.7, SD =
1.32). When looking at individual statements, it is interesting to note that students reported
having the resources to use Second Life (M = 5.44, SD = 1.93) but did not report Second Life as
being useful in their education (M = 2.92, SD = 1.48).
Table 5
Student Technology Acceptance to Second Life (17 statements; 5 constructs) (N = 716*)
Construct
n
707
M
2.74
SD
1.32
705
4.41
1.56
703
3.24
1.21
694
5.07
1.74
Behavioral Intentions to Use (3)
704
2.46
1.49
Total Mean (17)
715
3.47
1.04
*Note: Means were calculated using original data, not summated; thus, there is the potential for
all 716 student responses to be included in each construct mean.
Social Networking.
A review of responses related to social networking revealed that students perceive this
technology to be one that they can easily use (Effort Expectancy M = 6.09, SD = 1.00), plan to
use (Behavior Intentions to Use M = 6.49, SD = 1.09), and is supported by the institution
(Facilitating Conditions M = 6.59, SD = .81). However, the students do not see social
networking as beneficial to their education (Performance Expectancy M = 3.04, SD = 1.38).
Twitter.
Based on responses, students do not perceive Twitter to be useful to their education
(Performance Expectancy M = 2.33, SD = 1.26) and do not report intention to use the technology
(Behavior Intention to Use M = 2.79, SD = 1.91). Students reported neutral to slight agreement
regarding ease of use (Effort Expectancy M = 4.84, SD = 1.64) and institutional support for use
(Facilitating Conditions M = 5.68, SD = 1.64) of Twitter.
April 20-23, 2011
Table 6
Student Technology Acceptance to Social Networks (17 statements; 5 constructs) (N = 716*)
Construct
n
714
M
3.04
SD
1.38
712
6.09
1.00
710
4.91
1.05
705
6.59
.81
709
6.49
1.09
Total Mean (17)
715
5.21
.79
Table 7
Student Technology Acceptance to Twitter (17 statements; 5 constructs) (N = 716*)
Construct
n
712
M
2.33
SD
1.26
709
4.84
1.64
705
3.47
1.26
701
5.68
1.64
705
2.79
1.91
Total Mean (17)
714
3.65
1.10
Content Management Systems.
Content management systems were reported by students to be supported by the institution
(Facilitating Conditions M = 6.55, SD = .85), assist in their education (Performance Expectancy
M = 5.86, SD = 1.02), and to be easy to use (Effort Expectancy M = 6.11, SD = .88).
April 20-23, 2011
Table 8
Student Technology Acceptance to Content Management Systems (17 statements; 5
constructs) (N = 716*)
Construct
n
716
M
5.86
SD
1.02
714
6.11
.88
712
5.80
.99
707
6.55
.85
711
6.54
.87
Total Mean (17)
716
6.10
.75
Conclusions
a. Demographic background of responding agricultural students.
It can be concluded that the responding sample represents both male and female students along
with both undergraduate and graduate students. The male/female percentage of respondents
(33.7%/66.3%, respectively), while clearly including more females than males, reflected the
overall enrollment for Fall 2010 in the College of Agriculture that reported males at 48.9% and
females at 51.1% (Texas A&M University, 2010). Thus, the researchers believe that the
responding sample is representative of the broader population. Ethnicity was not taken into
consideration given that the broader population was predominately white (73%). The
respondents were evenly divided as to whether or not they had previously completed an online
course.
b. Technology awareness of students based on self-assessment.
Students overwhelmingly reported having quality Internet access at their homes and feeling
comfortable with computer technologies. Thus, it can be concluded that there are opportunities
to use emerging technologies to provide educational opportunities. Based on findings,
technology access or exposure is not a limiting factor in the use of technology for education.
However, it is important to note that a majority of students reported no use of blogs, Twitter, or
virtual worlds. It can be concluded that these three technologies are not in high use by this
population and that students may require more orientation to these technologies if they are used
for educational purposes.
c. Technology acceptance based on the UTAUT Model.
Technology acceptance can directly impact the adoption and use of technologies for specific
purposes. Findings reveal that students perceive each of the technologies studied (Second Life,
April 20-23, 2011
social networking, Twitter, and content management systems) as unique entities that vary in
regard to their personal acceptance. Students in this study have overwhelmingly accepted
content management systems as a technology that can assist in their educational efforts. On the
other hand, Second Life and Twitter were not accepted by these same students as technologies
that can assist in their education. While students were comfortable with the technologies and do
not report inability to use the technologies – they do not see value in the use of these
technologies for education. Additionally, social networks were reported by students to be in high
use – but not for educational purposes.
Implications and Recommendations
What do these conclusions mean for agricultural education and the use of emerging technologies
for instructional purposes? Based on findings, it is important to recognize that while instructors
may see value in using Second Life, social networks and Twitter as innovative, instructional
tools, results of this study indicate that students do not necessarily share that belief. Perhaps the
wisdom of Confucious (450 B.C.) and his statement of "Tell me, and I will forget. Show me,
and I may remember. Involve me, and I will understand" comes into play as students have not
yet tried blogs, Twitter and virtual worlds for educational purposes. If true, instructors will need
to consider strategies that will enable students to see and experience the value of utilizing these
technologies for learning purposes. These strategies may include providing support and
resources to assist students in mastering the technology as well as using the technology in ways
that add value to the learning experience that are apparent to the students.
Potential instructional challenges and opportunities were also revealed through these findings.
Use of emerging technologies can increase interaction that can involve the learner, enable a
deeper understanding of content, and enhance retention of content. However, without special
attention to how these technologies are employed in the learning environment, it is possible that
students will not achieve the gains described through simple lack of technology acceptance.
Emerging technologies continue to provide opportunities for enhancing the breadth and depth to
post-secondary educational programs. However, based on findings from this study, technology
acceptance related to Second Life, social networking, and Twitter for educational purposes are
lacking. Efforts to include these technologies in the classroom must take this lack of acceptance
into consideration. Fortunately, students reported that “ease of use” and “institutional support”
were not issues; thus, the critical part will be demonstrating the educational value of the
technology use.
This study adds to the body of scholarship related to educational delivery systems, improving the
effectiveness of agricultural faculty, and improving delivery models that are topics noted as areas
of needed study in the National Research Agenda (Osborne, 2007, p. 3). However, there is a
need to continue this line of research to determine the overall educational effectiveness of
Second Life and other emerging technologies. Shultz and Doerfert (2010) reported that although
students were familiar with Twitter, they did not use it on a regular basis. Once again, this study
noted that Twitter was not accepted by students as a technology that will assist them in their
educational endeavors. Additionally, Rhodes, Irani, et al. (2008) reported a high use of social
networking (85.2% on Facebook) and suggested that this level of use indicates a potential
opportunity for instruction using these tools. However, the results of this study did not support
April 20-23, 2011
that conclusion. Although students find personal value in social networking, they do not see
value in the application of this technology for educational purposes. Thus, implementation and
use of these technologies need to take into account how students perceive the technologies so
that appropriate activities and information is provided to encourage understanding of the
educational value in the use of the technology.
The theoretical foundation of this study noted that technology acceptance relates to predictions
of technology use and factors that can impact use (Lederer et al., 2000). Based on findings from
this study, it is important to recognize the lack of acceptance for using social technology as a
learning tool in education. This study used the Venkatesh et al. (2003) model that devised “core
determinants of intention and usage” (p. 425) related to technology acceptance (Unified Theory
of Acceptance and Use of Technology). Future research and application, as it relates to the
UTAUT model, must utilize the construct performance expectancy by seeking ways to impact
student perceptions and understanding of how certain technologies can assist in educational
gains. For example, instructors may find educational gains (requiring assignments that utilize
the technology) or personal gains (building personal networks or friend connections) of value for
students. Effort expectancy (ease associated with the use of the system) should be incorporated
into technology-based instruction through tutorial sessions to assist students with learning how to
use particular technologies effectively and efficiently. Social influence (an individual’s
perceived importance based on what they believe others perceive) could also be increased by
involving change agents or influential students in demonstrating the value of incorporating
emerging technologies into instruction. Facilitating conditions (the perceived value that the
organizational and technical infrastructure exists to support use of the system) could be improved
through additional or extra assistance from the instructor or computer lab personnel.
Understanding the behavioral intention of students can assist instructors in being more prepared
for student response to the use of emerging technologies.
The results of this study reveal questions for further research. Do students who are exposed to a
particular technology in class settings continue to use the technology outside of class or is it a
one-time experience? Does this exposure impact technology acceptance? Does acceptance vary
by use of technologies in a discipline? How does technology acceptance impact learning when
instructors utilize one of the technologies studied? Based on findings, one can conclude that it
will be critical to present the technology in a way that enables students to easily see the
educational benefits of using the technology. However, successful implementation may require
additional technology-specific considerations.
In regard to this study, it is recommended that the construct of facilitating conditions be revisited
to determine if future studies could include additional and/or alternative statements to increase
the reliability of that construct. Additionally, future studies should consider the three constructs
(i.e., attitude toward using technology, self-efficacy, and anxiety) that were determined by
Venkatesh et al. (2003) to not be direct determinants. It is possible that these constructs could
impact agricultural students and help educators utilize technologies more effectively.
April 20-23, 2011
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Attitudes and usage of students enrolled in a college of agriculture course. Journal of
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April 20-23, 2011
The Attitudes and Opinions of Agricultural Producers Toward Sustainable Agriculture on
the High Plains of Texas
Caitlin Frederick, Courtney Meyers, David Doerfert, & Jon Ulmer
Abstract
Agricultural producers face several issues in their operations including water
conservation, sustainability, legislation, and carbon sequestration. Understanding the issues
facing farmers, as well as the attitudes and perceptions producers have regarding these issues,
will provide a better understanding of how to help producers implement change within their
operations. The purpose of this study was to determine the attitudes and opinions toward
sustainable agriculture through focus groups with agricultural producers on the High Plains of
Texas. To achieve this purpose, this study used a qualitative approach with a series of four focus
groups conducted in different areas of the High Plains of Texas with 13 participants who were
directly involved in agricultural production. The study revealed that producers face many
issues, with water being the most significant. The producers did not agree on a specific term or
definition for sustainable agriculture, but each agreed that conservation and stewardship is of
upmost importance in production agriculture. Several producers have already adopted
sustainable agriculture practices without recognizing them as such. The most important aspect
that influenced the adoption of sustainable practices was profitability. Suggestions for
additional research based on this exploratory study are provided.
Agriculture is undergoing extensive changes in order to respond to a variety of global
factors – continued population growth, vulnerabilities of a fossil fuel-based energy system,
climatic shifts, uncertain economies, and political instability (University of California - Davis,
2010). The impact of these factors are consequently felt through rising prices, food shortages,
depletion of water sources, a declining natural resource base, declining economic capacity to
sustain rural communities and households, and loss of soil productivity and prime agricultural
lands to urbanization. Current and past agricultural practices have been successful in the United
States to provide a safe and healthy food supply. However, various agricultural practices are
scrutinized for their non-sustainable impact on the environment and natural resources (Texas
Department of Agriculture, 2010).
The High Plains of Texas has become one of the most intensive agricultural areas in the
United States. It is estimated that 30% of the cotton and 25% of the cattle on feed in the United
States are located in this area. Agriculture, which conservatively accounts for more than 40% of
the region’s economy, depends heavily on water for irrigation from the Ogallala Aquifer.
Agricultural change is happening in response to impending depletion of the aquifer, a rapidly
expanding dairy industry, the national mandate for biofuels, and unstable energy and grain prices
(Texas Department of Agriculture, 2010). Moore and Rojstaczer (2002) suggested that the
Texas High Plains is an excellent area in which to study agricultural issues because the area
offers a location where solutions can be found and then practices can be suggested to other
1
April 20-23, 2011
regions. To find and implement solutions, long-term research and focused educational and
outreach programs are needed. Diversified, integrated approaches to agriculture across multiple
ecosystems must be designed that are economically viable, environmentally beneficial, and can
produce needed yields of food, feeds, fibers, and biofuels without depletion of the resources
upon which they depend. These approaches are often described as sustainable agriculture
practices (Sustainable Agriculture Research and Education, 2009).
Sustainable agriculture is based upon three pillars: 1) to allow agricultural producers a
means to maintain profitability over the long term, 2) to promote stewardship of the natural
resources, and 3) provide quality of life to producers of all kinds. Farmers and ranchers
constantly seek new and innovative techniques and strategies to produce quality food, fiber, and
fuels in a sustainable manner (Sustainable Agriculture Research and Education, 2010). Because
the field of agriculture is broad and a wide range of alternative practices exist, the idea of
sustainable agriculture means different things to different people (Dunlap, Beus, Howell, &
Waud, 1992). According to the U.S. Department of Agriculture (USDA):
The term sustainable agriculture means an integrated system of plant and animal
production practices having a site-specific application that will, over the long term:
satisfy human food and fiber needs; enhance environmental quality and the natural
resource base upon which the agricultural economy depends; make the most efficient use
of nonrenewable resources and on-farm resources and integrate, where appropriate,
natural biological cycles and controls; sustain the economic viability of farm operations;
and enhance the quality of life for farmers and society as a whole (USDA National
Agriculture Library, 2007, para. 8).
Sustainable agriculture practices include: crop and grazing rotation, practicing
conservation tillage, planting cover crops, and managing insects and weeds (Sustainable
Agriculture Research & Education, 2009). Another aspect of sustainable agriculture is efficient
water conservation techniques, which “are essential to ensure the viability of Texas’ agricultural
industry” (Texas Water Development Board, 2004, p. 11). Water for irrigation is the largest
water use in Texas, accounting for 42% of the state’s water demand (Texas Water Development
Board, 2004). The increasing population in Texas poses a challenge in meeting the water needs
of the state, but many tools are available to help efficiently manage and conserve water (Sanger,
2005). These tools include irrigation nozzles that conserve up to 15% more water, tillage
practices, irrigation scheduling technology, and more drought-tolerant seed varieties (Texas
Water Development Board, 2004). Due to the reliance on the Ogallala Aquifer for much of the
water supply in the High Plains, water districts in the state are required to set desired future
conditions for their part of the aquifer to better manage the water supply. In order to meet these
conditions, some type of monitoring and enforcement practices must be designed. Esseks and
Kraft (1993) found that farmers who have already started to implement conservation practices
will be more likely to allow monitoring of the irrigation water they are pumping.
Sustainable agriculturalists also work to ensure a reduced carbon footprint and to
incorporate practices that promote stewardship of the land’s natural resources (Sustainable
Agriculture Research & Education, 2009). One way to achieve this is through carbon
sequestration, which is “the process through which agricultural and forestry practices remove
2
April 20-23, 2011
carbon dioxide (CO2) from the atmosphere” (U.S. Environmental Protection Agency, 2010, p. 1).
Sequestration activities can aid in the prevention of global climate change by increasing carbon
storage in trees and soils, preserving the condition of existing tree and soil carbon, and by
reducing emissions of carbon dioxide, methane, and nitrous oxide (U.S. Environmental
Protection Agency, 2010). Climate and energy legislation, commonly referred to as cap and
trade, passed the United States House of Representatives in June 2009 and is closely related to
the topic of carbon sequestration. According to the EPA (2010), cap and trade is based on three
critical principles: a cap on carbon emissions, complete accountability for the environment, and
simplicity of design and operation. The EPA stated a cap on carbon emissions is vital to the
protection of public health and protection of the environment.
The theoretical framework used in this study is based upon the diffusion of innovations
(Rogers, 2003) and the theory of planned behavior (Ajzen, 1991). “Diffusion is the process in
which an innovation is communicated through certain channels over time among the members of
a social system” (Rogers, 2003, p. 5). The diffusion of innovations theory recognizes that certain
attributes of an innovation will influence the rate at which the innovation is adopted. Change
agents can influence the rate of adoption of an innovation by recognizing these attributes and
increasing relative advantage, compatibility, trialability, and observability while decreasing
complexity (Rogers, 2003).
The theory of planned behavior was designed to help explain and predict human behavior
(Ajzen, 1991). This theory states that the intention to perform a behavior can be determined by
three factors: attitudes about the behavior, social pressures to perform or not perform the
behavior, and the perceived level of control an individual has to perform the behavior. This
theory recognizes that the combined influence of attitudes, subjective norms, and perceived
behavioral control are the best predictors of intent to perform a behavior, which is closely related
to actually performing the behavior. Generally, the more positive the attitudes and subjective
norms are, and greater the perceived behavioral control is, the stronger the intention to perform
the behavior (Ajzen, 1991). Therefore, producer attitudes toward sustainable agriculture
practices have an influence on the intent to perform those behaviors.
When attempting to influence adoption of production practices, prior research has found
that producer attitudes and conservation practices are closely related (Miranowski & Shortle,
1986; Doll & Jackson, 2009). When producers feel that their actions will positively influence
their profit, they are more likely to engage in activities that promote conservation and
preservation of the natural resources (Schneider & Francis, 2006). Wilson (1997) cautioned that
the factors that influence farmer participation in conservation programs are very complex and not
fully understood. Because farmers are often in tight financial situations, project planners and
researchers need to recognize the complexity of farmer attitudes and how those attitudes impact
farmers’ water usage (Ahnstrom, Hockert, Bergea, Skelton, & Hallgren, 2008). Bruening and
Martin (1992) found that groundwater and water quality issues are a great concern to agricultural
producers, and these producers said they would be better able to make efficient use of the water
supply if they were more educated about conservation practices.
The decision to adopt sustainable agricultural practices is also related to farmer attitudes
toward agriculture and environmental factors (Jones, 2003). Producers who had a postive
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April 20-23, 2011
attitude toward protecting the environment chose to adopt sustainable agricultural practices.
Huylenbroeck and Whitby (1999) indicated producers normally have a positive attitude toward
practices that promote sustainablity within agriculture. Producers’ positive attitude toward
sustainability indicated agricultural producers are concerned with environmental protection and
safety. Jones (2003) found that while producers’ showed concern for sustainability, ultimately,
the decision to adopt sustainable practices was based on economic success. In terms of attitude,
Shanahan, Scheufele, and Lee (2001) found producers made decisions to adopt new practices if
the percieved benefits were greater than the risks. If the new practice had the ability to
outperform the old, producers were more willing to accept the risks associated with the practice.
The National Research Agenda: Agricultural Education and Communication 2007-2010
(Osborne, n.d.) identifies the need to understand what information varied audiences need to make
informed decisions. The purpose of this study was to determine the attitudes and opinions
agricultural producers on the High Plains of Texas had toward sustainable agriculture practices.
The information gathered through this research provided a better understanding of why
producers make sustainability related decisions in their current operations. The following
research questions guided this study:
1. What are the characteristics of the selected agricultural producers of this study?
2. What are the problems facing agricultural producers in the High Plains of Texas?
3. What practices related to sustainable agriculture are producers implementing?
4. What changes do producers plan to make to diversify their operations?
5. What are agricultural producers’ perceptions of carbon sequestration?
This study used a qualitative research design with four focus groups to discover selected
agricultural producers’ attitudes and opinions of sustainable agricultural practices. The focus
group design is the best approach to answer the research questions of this study because “focus
groups can provide insight into complicated topics where opinions or attitudes are conditional or
where the area of concern relates to multifaceted behavior or motivation” (Krueger & Casey,
2009, p. 45). Most importantly, focus groups have the ability to generate data and insight that
may not be evident without group interaction (Morgan, 1997).
This study utilized snowball or chain sampling to identify people of interest who were
capable of providing in-depth information to answer the research questions. Contact information
was gathered from willing participants during area agricultural events, and those individuals
were contacted and invited via telephone to participate in this study. Selected individuals were
also asked to identify others who were also able to participate in the study (Ary, Jacobs, &
Razavieh, 2002). All potential participants were involved in agricultural production. After all
potential participants were contacted via phone, they were sent a formal invitation to attend the
focus group in their area. A total of 48 participants were contacted and asked to attend the
sessions. Morgan (1997) recommended over-recruiting for focus groups by 20%. The lead
researcher also contacted all potential participants via telephone the day before each group to
remind them of the session, provide details if needed, and determine if they would attend. These
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April 20-23, 2011
phone calls reminded those who may have forgotten about the group and reinforced the
importance of attendance (Krueger & Casey, 2009).
Four focus groups were held between May and July of 2010 within the High Plains of
Texas. Sessions lasted approximately two hours. Focus group size ranged from two to four
participants. Small focus groups, sometimes called mini-focus groups, work well because the
participants feel more comfortable speaking and sharing ideas. Smaller group sizes allow
participants more time to elaborate on ideas and encourage more discussion (Krueger & Casey,
2009). A moderating team was used to facilitate each session that consisted of two different
main moderators, who each facilitated two sessions, and two assistant moderators. The
moderator’s main focus is facilitation of discussion and assistant moderators operate audio
recording devices, respond to unexpected interruptions, and address other issues that may arise
(Krueger & Casey, 2009). Three small audio recording devices were used to capture all
discussion.
Focus group participants completed a general questionnaire before each focus group
session to collect additional information that would not be discussed during the session. The
questionnaire asked the age, production status, production areas, and water conservation
techniques of each participant. The moderator’s guide, used in all focus groups, was peerreviewed by a panel of experts familiar with focus group methodology and the purpose of this
study. The moderator’s guide included six topic areas that aligned with the research questions of
the study. Several planned probes were also included under each question to ensure quality
discussion among participants (Morgan, 1997). The focus groups began with the moderator
giving brief instructions and explaining the purpose of the research group. The opening question
allowed the participants to introduce themselves and briefly explain their agricultural operation.
The participants were also able to identify things they had in common with each other (Krueger
& Casey, 2009).
Next, the moderator began the introductory questions. These questions introduced the
topic of discussion and allowed the participants time to reflect upon the topic (Krueger & Casey,
2009). The first section of questions required the participants to offer their opinions about
sustainable agriculture and problems facing the agricultural industry. The moderator asked
participants a series of questions to encourage discussion of their opinions and attitudes
regarding general issues related to sustainable agriculture. Diversification of agricultural
production was the next topic discussed. This section of questions was designed to help
transition the session conversation into more in-depth issues that drive the study (Krueger &
Casey, 2009). Participants were asked what they had done, and what they plan to do to increase
the diversification of their agricultural operations.
The moderator then guided the discussion into the key questions about water
conservation to learn the specific beliefs, opinions, and attitudes of the participants regarding this
topic. Carbon sequestration was another key topic during this part of the focus group session.
Participants were asked to discuss their knowledge of carbon sequestration and the current cap
and trade legislation. Before the conclusion of each focus group, the moderator asked the
session participants to indicate if they would like to add anything to the discussion. The goal
was to uncover information that had not been discussed and to ensure that no pertinent topics had
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April 20-23, 2011
been overlooked. This final question sought suggestions from participants about what to modify
for future focus group sessions (Krueger & Casey, 2009).
After the focus group sessions concluded, the moderator and assistant moderator verified
that the session had been successfully recorded, then transferred the audio recording to a
computer and filed all consent forms, notes, and questionnaires. These final steps helped ensure
that all comments and notes would be easily identified for future analysis. The moderating team
also engaged in discussion to identify the most important ideas or themes that arose, and any
unexpected or unanticipated findings. Effectiveness of the questions and any need for revision
was also discussed (Krueger & Casey, 2009). Focus groups discussions were transcribed in their
entirety. NVivo 8.0 was used for data organization and analysis. This computer program allows
qualitative researchers to organize data in order to identify themes and key phrases. The
researcher looked for common themes, and grouped them into categories. As themes emerged,
they were compared to existing categories to look for common relationships. New categories
were created for distinct themes that did not fit existing categories.
Findings
RQ1: What are the characteristics of the selected agricultural producers of this study?
Focus group member characteristics were collected using a general questionnaire
provided to participants prior to beginning focus group discussion. Thirteen agricultural
producers participated in the focus group sessions. The first session had three attendees, the
second had two, and the third and fourth groups each had four participants.
The participants of the focus groups represented six different counties on the High Plains
of Texas. The producers utilized pivot, drip, and row water irrigation. Six of the participants
indicated that they raised livestock. Table 1 displays the demographic information collected
from the participants. The ages of the participants ranged from 25 to 71, with the majority of the
producers being 50-70 years old. One female attended focus group number two; the remaining
participants were all male. All but one participant indicated farming is their primary source of
income; the female responded no, but worked closely with agricultural producers and had family
who farmed full time. The participants all farmed at least 1,500 acres, and the largest producer
farmed 11,000 acres.
The participants had a total of 42,591 acres combined in their agricultural operations. Of
the total acreage, 23,842 acres (56%) receives no irrigation and 18,749 acres (44%) is irrigated
using various methods. Four of the participants used irrigation scheduling software to more
efficiently manage their irrigation. Cotton was the most produced crop by the participants with
20,000 acres (61% of total acreage), followed by wheat at 8,120 acres (25% of total acreage),
and grain sorghum at 2,040 acres (6% of total acreage). Sunflowers, grain corn, food corn, and
forage sorghum followed with less than 1,500 acres each.
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Table 1
Demographic Characteristics of Agricultural Producers Participating in Four Focus
Group, High Plains of Texas, 2010 (N = 13)
Is Farming
Total
Primary
Raise
Group
Participant
Age
Gender
Acres
Income
Livestock
One
1
40
Male
3,000
Yes
No
One
2
52
Male
1,840
Yes
Yes
One
Two
3
60
Male
1,500
Yes
Yes
4
71
Male
3,000
Yes
No
Two
5
33
Female
2,000
No
No
Three
6
68
Male
11,000
Yes
Yes
Three
7
67
Male
2,660
Yes
Yes
Three
8
51
Male
3,140
Yes
Yes
Three
9
62
Male
3,500
Yes
No
Four
10
63
Male
2,181
Yes
Yes
Four
11
53
Male
1,600
Yes
No
Four
12
57
Male
4,850
Yes
No
Four
13
48
Male
2,320
Yes
No
RQ2: What are the problems facing agricultural producers in the High Plains of Texas?
The participants indicated they faced several important problems. The water supply and
the Ogallala Aquifer were the most frequently mentioned and discussed. Legislation, policy,
technology, production costs, markets, and outward expansion were other problems facing the
agricultural producers. When the question, “What are the major issues facing agriculture
producers in this area?” was read aloud, the participants from group number one answered
“water” in unison. Similar responses were recorded at the other focus groups with the emphasis
on water as a major concern for participants. Because the issue of water was so important to
them, the participants were asked to elaborate and describe more about the water problem
currently facing the High Plains of Texas. The producers indicated that the current declining
condition of the Ogallala Aquifer will pose a threat to their operations because they depend upon
water for irrigation to increase their yields and profitability. If the Ogallala Aquifer were to
become unavailable for agricultural irrigation, producers’ profitability may be compromised.
Along with the topic of water conservation, participants discussed desired future
conditions, which are established by the water districts in the area. Most participants said that
some type of monitoring was necessary in order to ensure the stability of the Ogallala Aquifer.
However, some of the producers water monitoring may not be the correct way to approach the
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management of the groundwater. The participants did agree that local control was the best way
to accomplish desired future means goals.
Another area the participants mentioned as a problem they were facing was related to
government involvement in their operations through legislation, including legislation that deals
with water conservation. One participant said, “As water legislation goes, so there goes our
production.” The participants also expressed a general concern for potential legislation. As one
participant said, “We don’t know for sure what they are going to do in Austin or Washington,
D.C.” Environmental Protection Agency (EPA) regulations regarding fuel usage for equipment
were discussed, and a producer explained, “All those regulations are going to be adding to our
cost.”
When discussing policy, participants mentioned international trade and relations. One
producer said, “I would say that the international regulation part keeps me awake more than
anything else does.” Another producer added, “We’re not on a level playing field as far as
international economics are concerned and that’s going to be in the way for U.S. producers
because we’re darn efficient that we have an excess of goods.”
Technology was discussed as another problem facing agricultural producers in the High
Plains of Texas. Some participants said that the available technology was too expensive;
therefore, it did not allow them all an equal chance to experience the benefits. One producer
said, “They’ve made equipment do so much more work, but as a result that equipment is so
much more expensive.” Another participant added, “That’s hard on the smaller farmer.” Other
producers argued that the cost of the technology is worth the added efficiency and yields, even if
it is expensive to purchase. Others added that the increased technology has decreased the need
for paid labor.
Production costs were discussed throughout all four focus groups. Focus group
participants all commented at some point about production costs and how they affect their
production, profitability, and success in production agriculture. Production costs discussed
included: fuel, fertilizer, chemical, equipment, technology, energy, seed, labor, and irrigation.
The main theme that emerged was the high cost of fuel. The participants indicated that fuel
prices had a big effect on their operation because it is needed to plow, plant, spray, harvest, and
run irrigation motors.
Participants also mentioned markets for agricultural commodities as a problem they face.
This problem is based on the fact that farmers do not get to choose the price for which they sell
their goods. One producer said: “One realization I have is the fact that the farmers are on the
bottom of an economic situation. We accept what’s given to us and we sell in a market that’s
going to give us X number of dollars and that’s it.” The producers discussed the risk they have
invested into their operations and said that their high input costs made them vulnerable to the
volatile markets.
The main theme through all of these problem areas – water, legislation, policy,
technology, production costs, and markets – was the concept of profitability. All of the focus
group participants discussed profitability and expressed their concerns for the financial aspect of
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April 20-23, 2011
their operations. One participant stated: “Production agriculture is a business. We’re in it to
make a living and to provide capitol so that we can increase the efficiency of our business.” The
general theme from this discussion highlighted that most decisions producers make in their
operations are related back to profitability.
The focus group participants also expressed concern regarding outward expansion. The
producers all agreed that less land would be available for agricultural production as more people
moved to the rural areas. The producers said they would have to produce more on less land in
order to maintain their operations. Along with this problem is the perception of agriculture
among individuals who are moving from urban areas to the more rural areas. The participants
said the general public population does not understand how hard they work to efficiently use and
preserve available natural resources, which can impact the broader understanding of agricultural
practices.
RQ3: What practices related to sustainable agriculture are producers implementing?
The focus group discussion revealed that the majority of the producers were already
engaging in practices that were related to sustainable agriculture – they just were not aware they
were considered sustainable. Many of the producers were implementing processes such as
minimum till, no till, more efficient irrigation, soil conservation, diversification, crop rotation,
crop residue management, and precision technology.
When asked to define sustainable agriculture, the participants had a variety of responses.
One producer said sustainable agriculture meant organic. Another producer indicated that
sustainability was for the future while another explained sustainability as being “kinder or
gentler to the land.” A different producer described sustainable agriculture as survival. The
participants from focus group two did not like the word sustainability. One participant said:
“When I hear the word sustainable, it makes me think I’m doing just enough to hang on, making
just enough to keep the bank happy so they won’t foreclose. I hate the word sustainable. I love
the word profitable.” The moderator then asked if they preferred the word “stewardship.” The
participants agreed that stewardship was a better term to use in regard to agricultural production.
Although the terminology and initial opinions of sustainable agriculture were neither all
positive nor in agreement with the USDA definition, all the participants agreed that agricultural
producers should strive to preserve the natural resources and make efficient use of nonrenewable resources. The discussion indicated that the producers had already begun to
implement practices that would make their operations more sustainable and had increased their
efficiency through the use of technology. This need to improve efficiency was motivated by the
need to increase profitability and decrease production costs. One participant said, “We become
more environmentally friendly to become more economically productive.” Many participants
had moved away from using row water or flood type irrigation to using pivots and underground
drip systems. Others had already started implementing a minimum tillage system within their
operations and were utilizing crop rotation and residue management. The producers said that
when they implemented these changes, their crops grew better and their yields were higher.
9
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RQ4: What changes do producers plan to make to diversify their operations?
The participants discussed adopting practices such as new seed varieties, increasing their
use of technology, and adding livestock to their operations. Due to increased profitability,
several producers had already started to diversify their operations, which is a sustainable
agriculture practice. The producers seemed interested in using new seed technologies that would
allow for more drought resistance and protection against insect damage. One producer said, “If
we can get a cotton plant that can help resist insects, we can use fewer chemicals.” Another
producer commented, “Hopefully, we’ll have some crops that will require less water.”
Precision technology was also commonly used by the focus group participants. Increased
yields and profitability had encouraged these producers to start utilizing tractors equipped with
global positioning systems (GPS). Most participants said they could benefit from the use of
more technology. Technological advances allow the producers to accomplish more work faster
with less hired labor. One producer said he would “probably start using a little more technology
as far as irrigation scheduling.” Another producer said, “I think it’s going to be all the
technology and I think it’s all going to be driven by economics.” All of the producers agreed that
there was some type of technology they are not currently using that can help them become more
efficient and profitable. One producer said, “I know there are some new technologies that I
haven’t tried yet.” Another producer stated: “I’m convinced that agriculture is here to stay. The
technology is probably going to be our savior.”
Some of the producers indicated they would like to expand their operations with the
addition of livestock production, particularly the addition of cattle. The producers indicated it
was becoming easier to raise cattle in the High Plains of Texas due to the increased number of
permanent fences.
RQ5: What are agricultural producers’ perceptions of carbon sequestration?
Some of the participants did not fully understand the concept of carbon sequestration.
When asked what came to mind after hearing the term carbon sequestration, producers answered:
“bad”, “Al Gore”, “money”, and “I don’t know.” The discussion quickly moved from
sequestration itself to cap and trade. One producer elaborated to say, “I’m not into signing a
piece of paper that says I won’t plow for the next 100 million years or whatever.” The producers
said agriculture was not getting treated fairly in terms of carbon credits and legislation. Most
producers had a negative attitude toward cap and trade. Another participant argued that cap and
trade was positive for farmers, “They’re going start paying us for what I already do, minimum
tillage.”
Conclusions/Implications/Recommendations
Worldwide, agriculture is facing a number of serious issues in feeding a growing
population with dwindling natural resources and viable land. Sustainable agriculture has been
proposed as an approach to make agricultural practices more environmentally friendly and
economically feasible while producing the necessary amount of food, feed, fiber and biofuels
(Sustainable Agriculture Research and Education, 2009). This study sought to recognize the
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April 20-23, 2011
problems agricultural producers in one area, the High Plains of Texas, face and determine their
attitudes and opinions toward sustainable agriculture practices.
This study revealed that the selected agricultural producers in the High Plains of Texas
face many complex and intertwined problems – water, legislation, policy, technology, production
costs, markets, and outward expansion. Water was by far the most significant concern shared by
the participants. The producers are conscious of the depleting supply of water in the Ogallala
Aquifer, and most supported desired future conditions. All the mentioned problems are related
to profitability, except for outward expansion. The participants were very concerned about
issues that impacted their ability to successfully operate their agricultural enterprises. Within the
problem of outward expansion, it was interesting that the participants recognized the disconnect
many people experience regarding the production of their food and fiber. Although producers
are focus on the day-to-day success of their operations, they are also concerned with how
agriculture is viewed by others. The producers also said agriculture is a great means of carbon
sequestration, but agriculture is not given fair credit in the cap and trade legislation.
Previous studies have indicated that farmers’ attitudes toward sustainable agriculture
influence their decisions to adopt (Huylenbroeck & Whitby, 1999; Shanahan et al., 2001 Jones,
2003). Participants in this study had positive attitudes toward sustainable agricultural practices,
if not the term of “sustainable agriculture” itself. Similar to what Jones (2003) found, the
participants adopted sustainable agriculture practices due to the positive impact on profitability.
Within the diffusion of innovations (Rogers, 2003), relative advantage, which is “the degree to
which an innovation is perceived as being better than the idea it supersedes” (p. 229), is often
expressed as economic profitability. This demonstrates that the participants adopted the
sustainable agriculture practices due to the profitability (i.e. relative advantage) these techniques
provided. This implies that if an innovation is proven to be successful and shown to increase
profitability, then producers will be more likely to adopt the practice and continue to implement
the practice long term.
The participants also said they plan to increase their sustainability through future
conservation practices. The adoption of additional practices could be related to the attribute of
compatibility, which explains the level at which the innovation is consistent with past
experiences, values, and needs of potential adopters (Rogers, 2003). Because the participants in
this study had adopted sustainable agriculture practices and viewed them as sustainable, they are
more likely to adopt similar practices in the future.
Many factors can influence producers’ decisions to adopt agricultural practices (Wilson,
1997). As the theory of planned behavior demonstrates, intentions to perform a behavior are
influenced by attitudes, subjective norms, and perceived behavioral control (Ajzen, 1991). This
study focused on determining the attitudes selected agricultural producers had regarding
sustainable agriculture. Additional studies are needed to more fully explore this topic and
examine subjective norms, perceived control, and other intervening variables that may influence
adoption.
Based on the findings of this study, a decision making model was developed for
agricultural producers on the High Plains of Texas (Figure 1). This figure illustrates that
11
April 20-23, 2011
producers encounter two types of production variables – some that can be controlled and other
than cannot. From the participants’ feedback in this study, participants can control inputs related
to production costs, the use of certain technologies, and the amount of irrigation water.
However, they cannot control the market for their goods, water availability, legislation and
policy, or international influences. The participants in this study indicated that they consider
both types of factors then make decisions based on potential profitability. This figure should be
further refined and tested in future research with other agricultural producers.
Variables Impacting Production
Factors Can Control
Production Costs
Factors Can’t Control
Markets
- Seed
- Chemical
- Fuel
- Fertilizer
- Labor
- Equipment
- Prices
- Supply
- Demand
Water
- Rainfall
- Regulations
Technology
Legislation
- GPS
- Planters
- Irrigation Scheduling
Irrigation Water
- How Muc
- How Often
- How Applied
- Water
- Chemical
- Carbon
International Factors
- Trade
- Imports
Consider/Weigh Factors
- Exports
Profitable?
Make Decision Based on Profitability
Figure 1. Decision Making Model for Agricultural Producers on the High Plains of Texas.
This exploratory study is limited by the small number of participants who attended the
focus group sessions and the concentration on a limited geographic area. However, the results of
this study demonstrate the complexity of issues agricultural producers encounter. Future
research should be conducted using both qualitative and quantitative methods to further examine
how agricultural producers make decisions related to sustainable agriculture practices. These
results would benefit those who are attempting to encourage adoption of sustainable agriculture
practices. Data should also be collected from other stakeholders in the agriculture industry such
as production consultants and agricultural lenders to understand what influence they might have
as change agents or opinion leaders on the adoption of sustainable agriculture practices.
Research to develop recommended sustainable agricultural practices should also examine the
potential for economic profitability as this was an important attribute for producers in this study.
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The Use of Facebook as a Communication Tool in Agricultural-Related Social Movements
Mica Graybill, Courtney Meyers, David Doerfert, & Erica Irlbeck
Abstract
A social movement is a personal obligation taken on by an individual, due to either personal
experience or responsibility, to pursue action to implement a change in a community or society.
Facebook is a social networking tool in which users interact through online conversations and
build relationships by networking with other users. Facebook groups are created as part of a
smaller community within the social networking site to focus on particular interests, products, or
beliefs. The purpose of this study was to determine why individuals use social media,
specifically Facebook, to communicate information in social movements related to agricultural
issues. Eight semi-structured interviews were conducted with Facebook group administrators
who actively contribute to the promotion of an agricultural-related social movement. Results
found that the social movements did not exist before Facebook was used as a communications
tool. The Facebook group administrators were motivated to become involved with the social
movement due to personal experiences. Although Facebook is the primary method used to reach
target audience members, the participants said they use a variety of other communication
channels. Additional research should explore other social movements to determine the impact
social media has on communication efforts.
Communications is often cited for its role in creating change, and has been used since the
beginning of time to not only relay information, but also to convey knowledge and skill,
manipulate views and beliefs, and to develop connections and relationships among people (King,
2003; Rogers, 2003). Communication has played a major role in facilitating change in
agriculture in the past (Rogers, 2003) and suggests how new social media technologies could be
used to advance preservation of agriculture in the future, as well as to relay up-to-date
information to agricultural specialists about news, weather, stock prices and more (AndersonWilk, 2009)
Advancements in agriculture and technology have generated a crucial need for the
industry to effectively communicate agricultural issues to the public (Roth, Vogt, & Weinheimer,
2002). This communication often happens through social movements, which are defined as
personal responsibilities or commitments, initially created by a leader or an experience, in which
a strong belief is held and action is taken to attempt to implement change (Gerlach & Hine,
1970). Local advocacy communication, a subset of social movement communication, includes
efforts of advocates to communicate through publications, mailings, mass media, the Internet,
interpersonal contact, meetings, phone calls, demonstrations, and other media (McHale, 2004).
Another form of communication is through online communities and social media
websites, which have sparked one of the most significant social developments in society
(Experian Marketing Services, 2010). Social media are primarily Internet and mobile-based
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tools for sharing information, interacting, and building relationships among individuals. Forms
of social media include blogging, podcasting, video blogging, and online social networks. Each
of these is designed to give society a way to reach out and connect with others. People like to
engage in social media to feel like they are being heard and that their thoughts and feelings are
respected (Brogan, 2010). Some social media and networking websites offer practices to diverse
audiences while others focus specifically on certain hobbies and interests. Sites also vary in the
communication tools they offer to users including mobile connectivity, blogging, and
photo/video sharing (Boyd & Ellison, 2007).
Facebook is one of the most popular and universal social media and networking sites. In
2010, active users on Facebook have increased to more than 500 million. Users spend an
average of 20 minutes a day engaging in the site‟s interactivity and connectedness, and at least
half of the entire Facebook population logs in once daily (Kabani, 2010). Facebook has several
features including profiles, groups, pages, events, advertising, and applications. Profiles are how
people represent themselves to others. Users make their profile pages unique to their own style,
interests, and creativity. Groups are created by users and allow them to take part in smaller
communities within Facebook that support certain interests or beliefs that are shared by others
(Sweeney & Craig, 2011). Facebook groups give these individuals the chance to participate in
other activities and come across opportunities they otherwise may not have the advantage of
gaining access (Park, Kee, & Valenzuela, 2009).
Social media use has grown overtime and includes those who live or work in an
agricultural-related industry. Hoffman (2009) emphasized the role of social media in agriculture
by saying that social media use has become “more of a business responsibility than a luxery”
(para. 6). In a 2009 American Farm Bureau Federation survey of young farmers and ranchers,
among the 92% of participants (aged 18-35) who use computers, 46% regularly interact in some
form of social media (Hoffman, 2009). Producers who responded to that survey were using
Twitter, a social networking microblogging site, to share happenings from around the farm
(Hoffman, 2009). Google Maps and Google Earth are being used to help farmers plot their land
(Hest, 2008). Agriculturalists are also using video sharing sites such as YouTube to post videos,
commercials, news packages, and documentaries (Bradshaw, 2009.
The theoretical framework used in this study combined intentional social change theory,
social capital theory, computer mediated communication theory (CMC), and the uses and
gratifications theory. These theories address how intentional change can occur and recognize the
role of computer-mediated media as communication channels to support change efforts.
Intentional social change theory addresses a change agent‟s attempt to bring about proposed
change with specific objectives and goals (Sato, 2006). A change agent is an individual who
influences people‟s opinions regarding their decision-making process about innovation in a
direction that is considered desirable by the change agent or its company (Rogers, 2003).
Intentional social change theory states that people use their own ideas and thoughts to manipulate
the actions and opinions of others in a way that the outcome is seen as beneficial. Four main
characteristics of social change are: 1) it happens everywhere, but the rate at which change
actually occurs varies from place to place; 2) social change is most often intentional, but almost
always it is, however, unplanned; 3) social change creates controversy among individuals,
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organizations, or societies at large; and 4) some changes have more significance than others
(Macionis, 2001).
The second theory applied in this study was social capital theory. Social capital is a
concept most often used to refer to social economic status and how people use their resources to
succeed (Woolcock & Narayan, 2000). It is the knowledge and experiences that have been
gained from being members in particular social groups or organizations, jobs that have been
offered because of a certain status or contact, or even just contacts of those who have been
referred to as a friend of a friend. Social capital can almost always be associated with
networking (Woolcock & Narayan, 2000). Social capital theory states that the people we know
and keep in contact with will enhance our social status and will be called upon for material or
social gain. Social capital refers to the “norms and networks that enable people to act
collectively” (Woolcock & Narayan, 2000, p. 3). This applies to individuals and whole groups
or organizations as well. Research conducted over the past several decades (Foley & Edwards,
1999; Woolcock, 1998) indicated that social capital can be used a number of ways in order to
gain different benefits, such as engaging in social media to build personal relationships, or
networking with co-workers to improve working conditions.
The third theory used, computer-mediated communication (CMC), encompasses the use
of networks of computers and technologies to aid in interaction and communication. These
technologies include, but are not limited to e-mail, discussion boards and forums, instant
messaging capabilities, computer video conferencing, and other online databases (Romiszowski
& Mason, 1996). Research has implied that CMC can create change in the way people
communicate and interact with one another and can influence certain communication patterns
and social networks (Fulk & Collins-Jarvis, 2001). This statement basically implies that CMC
leads to social effects. CMC does not only set the foundation and create structure for social
relations, but is also the gap between relations that occur and the tool that individuals use to
bridge that gap (Jones, 1995).
The final theory used in this study‟s theoretical framework was uses and gratifications.
The uses and gratifications theory attempts to explain the uses and functions of media for
individuals, groups, and society. This theory discusses why people choose particular media to
fulfill certain needs and incorporate it in their lives in a way most beneficial to them. The theory
recognizes that users are goal-oriented in their media consumption and application (Katz,
Blumler, & Gurevitch, 1974). Blumler and Katz (1974) conducted the first research to explain
the connections between the audience‟s motives, media gratifications, and outcomes. In more
recent years, with the arrival of Internet, the perspective and study of uses and gratifications and
the role it plays in people‟s lives seems all the more relevant (Bumgarner, 2007). Audiences
have an important responsibility in obtaining messages they receive from the Internet because
they are actively seeking to receive certain information (Bryant & Zillman, 2002).
Many studies involving Facebook discuss how uses and gratifications theory can be
applied. Bumgarner (2007) found college students use Facebook to follow their friends‟ profiles
and to keep up with what their friends were doing. Joinson (2008) found Facebook users
develop a variety of uses and gratifications from social networking sites, including traditional
content gratification, communication, and surveillance. Raacke and Bonds-Raacke (2008)
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evaluated the impact that social networking sites, particularly MySpace and Facebook, have on
college students. The majority of students in this study were using these social networking sites
during a significant number of hours during their day for building new relationships and
maintaining existing relationships. Results also indicated several gratifications were met
including making new friendships, keeping in contact with old friends, or using Facebook as a
marketing or promotional tool (Raacke & Bonds-Raacke, 2008).
The National Research Agenda (NRA): Agricultural Education and Communication
2007-2010 (Osborne, n.d.) addressed the need to examine how emerging technologies can be
used to transfer information and encourage public participation. The purpose of this study was to
determine why individuals use social media, specifically Facebook, to communicate information
in social movements related to agricultural issues. To achieve that purpose, the following
research objectives were used:
1. Describe the characteristics of the selected participants of the Facebook groups that
address social movements related to agricultural issues.
2. Describe the selected participants‟ motivation for involvement with the selected
social movements.
3. Describe how decisions were made regarding communication channels used to
promote the represented social movements.
Methods & Procedures
A descriptive, qualitative research strategy was implemented for this study using in-depth
interviews with the administrators of eight purposively selected Facebook groups that discuss
social movements in agriculture. A qualitative study was determined to be the most effective
approach to obtain the quality of answers and information needed for the study. Qualitative
research can also be described as research about “person‟s lives, lived experiences, behaviors,
emotions, [personal] feelings, and feelings about organizational functioning, social movements,
cultural phenomena, and interactions between nations,” (Strauss & Corbin, 1990, p. 11).
Participants in the study were purposively selected. Purposeful sampling occurs when a
researcher specifically selects participants because of their characteristics and knowledge on the
topic being researched (Morse & Richards, 2002). The purpose of the study was to locate groups
that supported agricultural issues. Individual participants who had personal Facebook pages
were not selected for the study. To begin the sampling process, a search was conducted on
Facebook using the keywords “agriculture,” “farming,” “ranching,” and “animals.” Many results
were eliminated from participation in the study because they did not meet criteria set by the
researcher for the study. The criteria used to purposively select Facebook groups began with a
requirement that the group have at least 1,000 members. The requirement was used to select
groups that were reaching more individuals and perhaps had a broader scope than more regional
topics. The list was then narrowed down based on the following criteria: how often the
Facebook page was updated; the relative recentness of the information provided; and the
administrators‟ involvement in posting information. These criteria helped ensure that the
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selected Facebook groups were currently active and participating in the identified social
movements in agriculture. The administrator for each of the selected Facebook groups was then
contacted to serve as a participant in the study. The participants represented different sectors of
the agricultural industry, and all supported their agricultural topics instead of opposing them.
Once the potential participants were identified, they were initially contacted using the
Facebook e-mail-messaging tool, followed by an e-mail recruitment letter sent to the listed
contact e-mail for each administrator. Additional participants were identified using a snowball
sampling technique in which the potential participants recommended other people they knew
who might participate in the study. Through their recommendations, the researcher contacted
four other groups through the Facebook e-mail-messaging tool. Once participants agreed to be
interviewed and provided their phone number, the lead researcher contacted them to further
explain the study and schedule a time for the interview. Before beginning the actual interview,
all participants agreed to verbal informed consent information. Table 1 shows the different types
of groups that were involved in the study, and gives a pseudonym to protect the participants‟
identities.
Table 1
Characteristics of Facebook Group Administrators Interviewed for Study
Pseudonym
Shawn & Jill
Jeremiah
Mark
Dustin
Blake
James
Katherine
Mission
Members in Group
Watching practices of the United States Humane
Society
Taking a stand against the agenda of the United
States Humane Society
Shares the importance of telling agriculture‟s story
167,550
18,071
11,611
Created for people to share all aspects of
agriculture
A place to connect with farmers and ranchers
4,331
A place for farmers and ranchers to connect with
communities using social media
Aim to improve media‟s perception of U.S.
agriculture
1,848
2,334
1,631
Note. Membership numbers were as of September 24, 2010, according to each Facebook group.
A questioning guide was developed that consisted of 30 key questions (this manuscript
provides the results from a portion of the complete interviews). The questions addressed
demographic characteristics; motivation to join the social movements; communication channel
decision making process; opinions, attitudes, and beliefs related to using Facebook; and,
assessment of using Facebook to achieve goals related to the social movements. A panel of
experts familiar with qualitative research and in-depth interviews reviewed the questioning guide
to make suggestions for wording, structure, and order of questions. Between the dates of
September 6, 2010 and September 20, 2010, eight semi-structured interviews were conducted by
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telephone with participants who lived throughout the United States. Each interview was
conducted using the same questioning guide and lasted approximately 45 minutes.
The telephone interviews were recorded using a digital recording device and hand-written
notes. The lead researcher transcribed each of the interviews and then analyzed the results using
NVivo 8.0 data management software designed to help store and analyze qualitative data. The
lead researcher coded the interview transcripts first using descriptive coding (Morse & Richards,
2002) to identify demographic characteristics of the respondents. Then, topic coding was used to
identify the material related to a topic that could be later retrieved and categorized. Finally, the
data were coded using analytic coding to examine the categories and develop themes to address
each research objective (Morse & Richards, 2002).
To establish research rigor, the researchers followed Lincoln and Guba‟s (1985) aspects
of “trustworthiness:” credibility, transferability, dependability, and confirmability. Credibility
determines how accurately the thoughts and opinions of those involved were depicted and
represented by the research (Ary, Jacobs, & Razavieh, 2002). This study demonstrated
credibility by using the opinions, beliefs, and attitudes directly from the sources as the raw data.
Transferability refers to the ability to generalize qualitative findings, which is how well the data
can be applied to different people in different situations at different times (Lincoln & Guba,
1985). The data collected in this study could be applied to similar types of social movements
that use Facebook as a communication channel. Dependability ensures that the results are
reliable, and over time, will remain consistent and trustworthy (Morse & Richards, 2002).
Dependability was established by keeping a record of the research through interview notes and
files (Foster, 2004). Confirmability is demonstrated when the data are supported by the primary
researcher and other researchers (Morse & Richards, 2002). Confirmability was established not
only by the direct information obtained by the primary sources, but also by citing other studies
and research that has been conducted on similar topics.
Findings
Objective 1: Describe the characteristics of the selected participants of the Facebook groups
that address social movements related to agricultural issues.
Each of the participants was an administrator of a Facebook group that represented
agriculture movements. Of these groups, three of the eight participants were paid to administer
their Facebook page as a part of their jobs. The other participants started their Facebook groups
and advocate voluntarily. In order to gain a better understanding of the study‟s participants,
demographic questions asked age, gender, and geographical location. The mean age was 30
years; the median age was 28 years; the mode was 40 years of age. Six of the participants were
male and two were female. Although all the participants represented Facebook groups within the
United States, the geographic locations varied. Three of the participants resided in Washington
D.C., while the other five participants lived in different locations across the United States,
including Arkansas, Missouri, South Dakota, Ohio, and California.
The participants had either completed a bachelor‟s degree or master‟s degree, or were in
the process of completing a bachelor‟s degree. Participants were also asked to give a brief
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explanation of their professional background. All of the participants were involved with the
agricultural industry either directly or indirectly; five of the participants were agricultural
producers, while the other three were employed by an agricultural organization.
During the interviews, participants were asked when their Facebook groups were formed.
Each of the Facebook groups was formed within the last two years – the oldest was initiated in
April 2009, and the most recent started in May 2010. The majority of participants had been their
group‟s administrator since the group was founded. Most participants indicated that their
primary responsibility to their Facebook group or fan page was to update the page with new
information and content, and to monitor what is being posted by members. Some participants
also said that they create links between the articles and information being posted to Facebook,
Twitter, blogs, and websites. Several participants responded that their main concern is to inform
people about important issues. One participant said his mission was to “keep members
motivated and communicating about agriculture.”
Objective 2: Describe the selected participants’ motivation for involvement with social
movements.
Personal experience was a prominent theme related to what first motivated the
participants to become involved in the cause they were advocating. Six of the eight participants
said they were encouraged to join the specific cause due to personal experiences. For some
participants, this experience was a negative one that affected them and being involved in a social
movement or cause helped them tell the other side of the story and share their own experiences.
One participant said he had a videographer tape a farm near his family‟s farm and then expose
the footage in a negative light. Blake said: “About five years ago, some anti-ag activists got
some undercover video of a farm we knew well. I then realized how quickly and easily they
could turn the perception of farm life around into a negative aspect.”
Another theme that was noticed among participants is that five of eight participants are
invested in their cause because it is something that has been instilled in them their entire lives.
Mark said: “For us, supporting this cause is very personal. Both my wife and I have grown up
around agriculture, and we love it very much.” Other participants commented about farming and
ranching being their livelihood for as long as they can remember. Having grown up around
agriculture has instilled a passion and motivation to promote the industry. Jeremiah said, “When
it comes to agriculture, it is something I have been a supporter of my whole life.”
Another theme for motivation for involvement in the cause is the desire to see the
movement succeed in the future. Several participants mentioned that they are involved in
actively promoting their cause for their children and for future generations to come. The overall
message from participants was that if they do not fight in favor of agriculture now, future
generations will suffer, which means that it will affect their children. Blake said, “Agriculture is
something that, like most farmers, I really enjoy and at very least, I try to make sure when I have
kids someday that they have the same opportunities that I did.”
Participants were asked to describe how they can be committed to their cause. Several
participants commented that the most important way they can be committed is by making sure
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consumers and producers have the most accurate facts and information. Participants said they
want to make sure they can stop rumors from being started if they actively continue to advocate
and give people information. Participants also noted they like to have face-to-face conversations
with people to advocate for their cause because having actual conversations with people can
initially open doors to get them interested in being a part of the cause. Jeremiah said: “It‟s just
talking to them and seeing what they actually know. Then it‟s my duty to give them the basic
facts and encourage them to do what they can in support of agriculture.”
Participants said their commitment to their cause involves sharing their story with others
so that people like them will want to share their story as well. Participants said that they find this
a good opportunity to encourage agriculturalists to take a stand for a cause that affects them
personally.
Participants had specific emotions or opinions that drove their involvement in support of
their movement or cause. Participants were angry when people do not know the facts behind
agriculture and fight against the industry. Shawn said, “I get angry when I see these things that
are unfounded coming from people who have absolutely no idea what it‟s like being a farmer.”
Sympathy was another emotion commonly expressed by participants. Several participants said
they feel sympathy for people who are being taken advantage of and do not know the facts.
Katherine said, “It is a terrible feeling when there is an attack on people and the industry from
people who are uneducated.”
In order to better understand why the participants were using Facebook for their causes,
they were first asked why they personally joined Facebook. Participants said the decision was
due to social pressures to communicate and stay in touch with family and friends. They said
Facebook is a good way to keep in contact with people they would otherwise lose touch with. It
was a good way to network and meet people they may never have an opportunity to come in
contact with. Another reason for personally joining Facebook was for professional use. Some
participants saw it as an opportunity, and said they thought joining would be a good tool to
embrace for their careers.
When asked what motivated them to use Facebook to promote their movement or cause,
participants indicated that Facebook actually allowed their cause to exist. The creation of the
Facebook groups provided a communication channel for the promotion of the social movement.
None of the social movements in this study existed before the creation of the Facebook groups.
Because the participants had been using Facebook for personal reasons, they were familiar with
how groups or fan pages could be used to promote or support their cause. They applied that
knowledge to create their own Facebook groups for their social movements.
In addition, participants said they chose Facebook because many other organizations
were already using it and so many people were already participating in this social networking
site. The visible success of other Facebook groups encouraged the participants to utilize
Facebook to promote their causes. Shawn said:
We first looked at Facebook to see what other people were doing. One thing is
PETA had something like 650,000 Facebook fans, and at the time I thought,
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“They are exceptionally good at organizing grassroots.” I thought that was an
impressive number of people to reach through technology.
To participants in this study, Facebook seemed to provide the most efficient forum for
people who wanted to engage in issues and discussions about the movement or cause. People
need a place to talk to others who share the same beliefs, and participants said Facebook had the
most users within their target population. Jill said:
A lot of people who are fans of ours are actually the older demographic, which is
currently the fastest growing demographic on Facebook. They are finding out
that it‟s a way they can get online and engage in issues they care about.
Objective 3: Describe how decisions were made regarding communication channels used to
promote the represented social movements.
Participants were not only promoting their causes through Facebook, but through several
other communication channels. Along with Facebook, participants used Twitter, YouTube,
blogs, websites, podcasts, articles, newsletters, and word of mouth to promote their causes and
movements. Though these are only a few communication channels, participants said they are not
limited to any one communication channel; they will use anything that can be effective in
spreading their message. When asked why each participant chose particular communication
channels to communicate with their members, the most common theme was that the tools being
used are free. Some of the groups represented are non-profit and do not have funding to do
advertising. Many of the social media platforms and online communication forums are free, so
organizations are not hurting themselves by trying each one out to see which, if any, will be most
effective. Shawn said, “We are always measuring the efficiency of communication vehicles in
terms of „cost per click‟ or „cost per eyeball.‟”
Another common theme was that the communication tools were well known among the
target audience, and were already being used by many different people. Katherine said, “We
chose the communication channels we use because they are the most well known and have the
most users, which makes them most applicable to us.” Participants indicated that they were
already noticing who was using what forms of communication channels, which had a major
impact on what communication channels were chosen. Overall, participants agreed that the
chosen communication channels were effective in promoting their social movements. Shawn
said, “If something wasn‟t working for us, we wouldn‟t be wasting our time with it; we would
have already moved on and tried something else that would get the job done.”
When evaluating the effectiveness of Facebook as an effective communication channel,
the determining factor for participants was the number of users who were already on Facebook.
Blake explained: “The biggest factor for me was the fact that there were already 500 million
users on Facebook. That shows that it‟s a place where people are going for information.” Others
said the number of users was an obvious reason for them to be utilizing the benefits of Facebook.
With so many people already on Facebook, it seemed that information provided on the site in
support of causes or movements would reach people one way or another. Jeremiah said: “You
put stuff out there, and people are going to find it; if they believe in it, they are going to follow it.
It obviously reaches a large number of people; there is no question in that.”
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Another emerging theme among factors of believing Facebook would be effective is the
fact that so many people were urging the participants to take part in it. Participants said that if
other organizations were urging its use, and they had been successful in their efforts, then it
would be a good tool to embrace. Blake said: “If you look at a lot of anti-agriculture groups,
they are using those tools as free PR and actually to further spread their message. If they are
making use of it, it should be the same for us.”
Participants promoted their Facebook groups or pages by inviting friends and people
through the friend finder tool. This method is quick and relatively simple, and has been an
effective way for some of the participants to get a jump-start on promoting their movement
through Facebook. Some participants also used advertising as a way to promote their Facebook
pages. Participants stated that they use any advertising they can afford. Several participants
commented that they promote their Facebook pages on their YouTube or Twitter accounts,
especially if they are targeting the same audience.
When participants were asked how frequently their pages were maintained, they agreed
that updates to Facebook pages should be made no less than two times a week. Some
participants said it was important to update the Facebook page as often as possible (Shawn
indicated that he posts every couple of hours) while some participants said posting too often
could be counter-productive. Participants said that when new information is posted on the
group‟s Facebook page, members most often comment and respond to information if it is
something they view as important and care about. Several participants agreed there will be key
players who are very active and comment often, and many members visit the page and get
information, but may never make a comment. When asked how trustworthy the information is
on Facebook pages, participants indicated that they closely monitored information being posted
by others to make sure the information is accurate and is not negative toward the mission of the
cause or movement. Some participants indicated that they had others help them monitor and
update their Facebook pages.
Conclusions, Implications, & Recommendations
Overall, participants represented different demographic characteristics related to age,
gender, and geographical location. The average age of participants was 30, and six of the eight
participants were male. Participants‟ geographic locations were representative of various regions
across the United States. When speaking in terms of educational backgrounds, all participants
either had a college degree or were in the process of obtaining a degree. All of the participants
were involved with the agricultural industry, either directly or indirectly; five participants were
producers in the industry, while three were employed by an agricultural organization. Each of
the Facebook groups had been created within the last two years, and the participants were the
key representatives of each group either as participant, founder, or both. Participants‟ main
responsibilities for managing their Facebook group included maintaining the page, updating new
information frequently, and monitoring what was posted on the page.
As Anderson-Wilk (2009) noted, communication has had a significant influence in
facilitating change in agriculture in the past and new social media technologies could be used to
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advance the field of agriculture in the future. Social movements in agriculture are necessary to
advocate on behalf of strongly held beliefs or actions. These advocacy movements utilize
various forms of communication (McHale, 2004) including social networking sites that allows
members to reach out, connect with others, and feel like they are being heard (Brogan, 2010).
Those involved in agricultural pursuits are using social networking sites to share and find
information (Bradshaw, 2009; Hest, 2008; Hoffman, 2009).
Participants in this study feel strongly about their cause or movement because an
experience or incident influenced their emotions and opinions. Intentional social change theory
recognizes the role these change agents (Rogers, 2003) have in using their own ideas and actions
to influence people‟s opinions in order to bring about the desired change (Macionis, 2001).
Using social networking sites, such as Facebook, helps create social capital (Woolcock, 1998;
Foley & Edwards, 1999). Social capital theory states that the personal relationships one has can
be used to achieve some desirable outcome. It is important to note that the social movements
explored in this study did not exist before Facebook. The social networking site allowed the
motivated individuals an avenue to share opinions, stories, and information. As uses and
gratifications theory states, people choose particular media to fulfill certain needs and will utilize
that media in a way most beneficial to them (Katz, Blumler, & Gurevitch, 1974). Prior studies
have found several gratifications associated with Facebook use including content gratification,
communication, surveillance (Joinson, 2008), making new friendships, keeping in contact with
old friends, or using Facebook as a marketing or promotional tool (Raacke & Bonds-Raacke,
2008). Facebook was selected by the participants because they were familiar with it as a
communications tool, noticed that other organizations were successful using it to reach audience
members, and it was free.
In addition to Facebook, participants used other different communication channels to
promote their social movement. Many of these, such as Twitter, blogs, and websites, are
computer technology-based and the theory of computer-mediated communication recognizes that
these technologies can be used to build social relationships (Jones, 1995). The participants said
these communication channels were chosen based on their ability to provide awareness, help
increase memberships within the groups, share information about the cause, and allow people to
have a central place to discuss topics and issues. Participants said they believed that their
Facebook groups are effectively reaching their audience members and providing beneficial
information related to the social movements they are promoting.
Based on the findings from this research, it would be in the best interest of agricultural
communicators to utilize Facebook, along with other social media tools, to communicate
agricultural issues to the public, and to promote social movements. Although Facebook is
limited by only reaching those people who are using it, this audience is large (500 million
people) and Facebook and has the capability to disseminate information at an extremely efficient
rate. It is a free tool that does not have any sign-up or annual fees. Others who are considering
using Facebook should follow best practices for using this communication tool. (Additional data
were collected from these participants regarding these best practices; this information will be
provided in another manuscript.)
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This study does have several limitations that should be recognized. First, the study is
limited to the purposively selected participants of the Facebook groups included in the study. As
in the nature with qualitative research, this purposive approach makes generalizability
impossible, although the results can be “transferred” to similar cases (Lincoln & Guba, 1985).
The study is also limited to studying one social networking website, Facebook, when many
others are available.
The purpose for this study was to gain insight on how communicators are utilizing
Facebook to promote social movements. Because the use of social media is still relatively new,
additional research is needed to determine why people are using it, and how to effectively market
a group or cause through Facebook or other social media tools. It would be useful to gain
updated information on computer-mediated communication (CMC) and to explain the effects of
why people use this particular form of media to interact with one another. If it was better
understood why people use social media and what they are hoping to gain from their
experiences, future communicators can more effectively target their messages to their audience
segments.
The administrators made assumptions based on what they thought they thought their
audience members wanted or needed in regard to information, but a better understanding of their
audience members would further improve the effectiveness of their communication efforts. A
quantitative survey with people who are members in these Facebook groups should be conducted
to help determine why people use it and what benefits they gain by engaging in Facebook. This
study should also explore the types of groups or fan pages people join and why they join them.
The question is raised as to whether people who join these groups are really a fan of the group, or
if they have other motivations for joining. An example of this would be if people joined a group
simply because their friends were joining the group. By conducting research with the members
of the group, it would help identify the users and gratifications of the members based on their
own perceptions and experiences.
Social movements in agriculture have existed for centuries (Sato, 2006); the use of social
networking sites to influence social change is a relatively new undertaking. It was apparent from
this study that Facebook allowed these movements to exist, which is in itself evidence of the
significant impact this social networking site has had in today‟s society. Additional research and
development of best practices will further refine the use of social networking sites to encourage
desired changes in many areas, including agriculture.
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Using the Health Beliefs Model to Comparatively Examine the Welding Safety Beliefs of
Postsecondary Agriculture Education Students and their Non-agricultural Education Peers
Shawn M. Anderson, Oregon State University
Jonathan J. Velez, Oregon State University
Ryan G. Anderson, Iowa State University
Abstract
The purpose of this descriptive correlational research was to investigate postsecondary
agriculture students’ perceptions regarding the safe use of agricultural mechanics equipment.
Students enrolled in a university metals and welding course were surveyed using an adapted
instrument to assess constructs of the Health Beliefs Model, self-efficacy for learning, and selfefficacy for safety. The respondents (N = 117) were separated according to major with 18.8 % (n
= 22) representing agricultural education preservice teachers. Findings showed that
agricultural education students felt more susceptible to safety accidents and had a lower selfefficacy for learning and self-efficacy for safety. Correlations were found between four
constructs: perceived susceptibility, perceived barriers, self-efficacy for safety and self-efficacy
for learning. This study revealed that students perceive safety instruction as vital in a metals
and welding course. Positive correlations between perceived susceptibility and self-efficacy for
safety revealed that the more students know about the potential risks associated with the metals
laboratory, the more confident they feel with performing the safety habits. Results identified
several key opportunities to improve the safety of both students and instructors. The safety
training of agricultural education preservice teachers is vital to the safe and effective operation
of agricultural mechanics laboratories.
Introduction
Agricultural Mechanization Courses have been and remain a popular choice among
students in both secondary and post-secondary education. Teachers of these courses often
employ “learning by doing” techniques through the utilization of agricultural mechanization
laboratories. Bruening, Hoover, and Radhakrishna (1991) indicated that of all of the duties an
instructor of a laboratory based class performs, the physical safety of students must come first
over what students learn. Miller and Gliem (1993B) found that high school administrators
indicated that instructors must make safety one of their top priorities and insisted teachers also
model safe practices.
Laird and Kaher (1995) reported that agricultural education instructors considered safety
to be the most important unit of instruction in a mechanization laboratory. Miller and Gliem
(1993A) indicated that agricultural mechanization laboratories were found to be safe, considering
the nature of the facility. However, they also noted that 20% of all student accidents were a result
of injuries sustained in a mechanization laboratory. Secondary agricultural education teachers
have cited agricultural mechanics as one of their largest areas of need (Saucier, Tummons, Terry,
& Schumacher, 2010). Along with overall safety, Dyer and Andreasen (1999) identified the
importance of student and teacher attitudes in establishing a climate of safety. Based on the
established importance of safety and the role of student and teacher attitudes, the current research
1
April 20-23, 2011
study sought to determine perceptions related to both safety and self-efficacy. An examination
of the safety and self-efficacy perceptions of those students enrolled in agricultural mechanics
courses may aid faculty in designing, developing and assessing this key program in agricultural
and life sciences. The National Research Agenda for Agricultural Education and
Communications, postsecondary settings research priority area four recommended research
which addresses the effectiveness of educational programs and their graduates, in agricultural
and life sciences (Osborne, 2007). Exploration of student perceptions of, and the relationships
between, student safety and self-efficacy may provide the necessary data for programmatic
improvements.
The agricultural mechanization laboratory possesses several potentially hazardous places
for both students and instructors. It is the teacher’s responsibility to oversee inexperienced
students to ensure that the students are minimizing their risk for potential injury (Dyer and
Andreasen 1999). Although teachers have identified safety as a primary concern while managing
an agricultural mechanization laboratory; it was noted by Dyer and Andreasen that safety
violations still existed. Lawver and Fraze (1995) identified agricultural education instructors had
positive safety attitudes, however their teaching practices did not reflect their attitudes.
This research study is intended to elucidate information critical to the formation of safe
attitudes and practices. If researchers can determine ways to improve the safety of both students
and instructors, agricultural mechanics laboratories will be one step closer to becoming safe and
effective learning environments. In an effort to examine variables relating to safe beliefs, the
researchers utilized the Health Belief Model (HBM) developed by Hochbaum in 1958.
Theoretical Foundation
The Health Belief model grew out of the concern regarding the limited success of health
programs in the 1950’s (Strecher & Rosenstock, 1997). The model has been widely used to
predict participation in health screenings, immunizations, HIV prevention, and safety behaviors
(Hodne, Thu, Donham, Watson, & Roy, 1999). According to Abraham and Sheeran (2007), the
constructs of the HBM have, “. . . usually been operationalized as a series of up to six separate
independent variables which can be used to predict health behaviors.” (p. 97). Figure 1 details
the original formulation of the HBM. The major elements of the model were perceived
susceptibility (likeliness to become ill), perceived severity (potential for causing personal harm),
perceived benefits (belief in the value of reducing the threat), and perceived barriers (physical,
psychological, or financial costs). The model also included cues to action or relevant stimulus
that must occur in order to trigger the appropriate health behavior. In the 1980’s self-efficacy
was also added to the HBM (Sharma & Romas, 2008).
The original Health Beliefs Model contained six constructs including perceived
susceptibility, perceived severity, perceived benefits, barriers, cues to action, and self-efficacy.
The first construct, perceived susceptibility, refers to an individual’s perception of the risk of
developing a health condition (Sharma & Romas, 2008). In the case of agricultural safety, this
dimension refers to the individual’s perception of getting into an accident. On one extreme, an
individual may deny the possibility of getting into harm’s way or beli

Western AAAE Research Conference Proceedings

Transcription

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