Acceptance and Usage of Mobile Devices for Informal English

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College of Education EdD Project Papers
College of Education
Spring 4-1-2016
Acceptance and Usage of Mobile Devices for
Informal English Language Learning in the
Japanese University Context
Daniel J. Mills
University of Wyoming
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Mills, Daniel J., "Acceptance and Usage of Mobile Devices for Informal English Language Learning in the Japanese University Context"
(2016). College of Education EdD Project Papers. Paper 3.
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To The University of Wyoming:
The members of the Committee approve the dissertation of Daniel J. Mills
presented on March 9th, 2016
Dr. Doris U. Bolliger, Chairperson
Dr. Jason D. Hendryx, External Department Member
Dr. Craig E. Shepherd
Dr. Cliff Harbour
Dr. Qi Sun
APPROVED:
Dr. Mary Alice Bruce, Department Chair, Professional Studies
Dr. Ray Reutzel, Dean, College of Education
Mills, Daniel J., Acceptance and Usage of Mobile Devices for Informal English Language
Learning in the Japanese University Context, Ed.D., Department of
Professional Studies, May 2016.
The researcher investigated the acceptance and usage of mobile devices for the purpose of
English-language learning among Japanese university students. The study was conducted at a
private university in Japan. A paper-based instrument was distributed to undergraduate students
enrolled in 59 required English as a foreign language courses. The survey included four
sections: (1) acceptance of mobile devices for informal English learning, (2) usage of mobile
devices for informal English learning, (3) demographics, and, (4) open-ended questions. Nine
hundred and seventy-seven students participated in the study. The results of the study showed
that Japanese university students were open to the use of mobile devices for informal Englishlanguage learning and were already using the devices for this purpose to listen to Englishlanguage music, and to access dictionary and translation applications. However, applications
that would enable students to engage in communicative practice, such as social networking sites,
were underrepresented. Furthermore, while participants were positive regarding the portability
and convenience of the devices for informal learning, they were concerned about health issues
related to their usage and worried that mobile learning may not be as effective as traditional
methods of study. The results of a Pearson Product Moment Correlation test demonstrated that
each of the six subscales of acceptance, as well as the total scale, was significantly correlated
with the usage measure; the total acceptance scale was also significant correlated with
participants’ reported usage of mobile devices. Further analysis revealed that individual
differences had an effect on participants’ acceptance and usage responses.
ACCEPTANCE AND USAGE OF MOBILE DEVICES FOR INFORMAL ENGLISH
LANGUAGE LEARNING IN THE JAPANESE UNIVERSITY CONTEXT
by
Daniel J. Mills
A dissertation submitted to the University of Wyoming
in partial fulfillment of the requirements
for the degree of
DOCTORATE OF EDUCATION
in
INSTRUCTIONAL TECHNOLOGY
Laramie, Wyoming
May 2016
copyright page
© 2016, Daniel J. Mills
i
Acknowledgements
When I first began work on my doctorate, I questioned several people who had
completed the degree for their advice. Almost everyone I spoke with told me that their success
was due in large part to the support of their family, friends, colleagues, and professors.
In my journey to complete my doctorate, my wife, Megumi Kohyama, was always there
for me. She encouraged me everyday to do my best, but also reminded me to have fun along the
way. In addition to providing moral support, she helped me immensely through her skills as a
translator and her expert knowledge of Excel. I never would have accomplished this goal
without her.
My colleagues Sean Toland, Sean Gay, and Brett Morgan spent many hours proofreading
my manuscripts, and Jeremy White was always available for a chat, and to lend me his
whiteboard, when I was working on a difficult problem. My supervisors at work, Professors
Virginia Peng and Michelle Kawamura were instrumental in helping me in my data gathering
efforts. Dr. Tonia Dousay went out of her way to help me by answering my seemingly endless
questions and always being there to let me know it would be all right. I am also thankful to Dr.
Glenn Stockwell who took the time to provide me with feedback on my research project and
share his thoughts on future research possibilities.
Finally, I would like to thank the members of my committee. In particular, Dr. Bolliger
has served as a brilliant mentor to me throughout this entire process. Many of my colleagues
who are completing their doctorate degrees are jealous of how lucky I am to have her as my
advisor and chair of my committee. The other members of my committee, Drs. Shepherd,
Hendryx, Sun, and Harbour, have all taken time to support me along the way by answering my
ii
questions, providing me with pertinent references and ideas, and meeting with me to discuss my
research whenever I was visiting campus. Thank you so much for all you have done for me.
At times my journey towards completing my doctorate has been challenging. However,
because I was passionate about what I was doing and had the support of so many incredible
individuals, I have always felt lucky for the experience. Now, I look forward to the next chapter
in my academic life.
iii
Table of Contents
Acknowledgements ..................................................................................................................... ii
Table of Contents ....................................................................................................................... iv
List of Tables ............................................................................................................................ vii
List of Figure............................................................................................................................ viii
Chapter 1: Introduction to the Study ........................................................................................... 1
Background ............................................................................................................................. 2
Mobile-Assisted Language Learning ...................................................................................... 4
Conceptual Framework ........................................................................................................... 4
Research Problem ................................................................................................................... 5
Purpose of This Study ............................................................................................................. 6
Research Questions ................................................................................................................. 6
Study Significance .................................................................................................................. 7
Methodology ........................................................................................................................... 8
Researcher’s Role and Motivation .......................................................................................... 9
Definitions............................................................................................................................. 10
Summary ............................................................................................................................... 11
Chapter 2: Review of Literature ............................................................................................... 13
Introduction ........................................................................................................................... 13
The Japanese Educational Context – Policy, Practice, and Technology .............................. 13
Second Language Acquisition .............................................................................................. 18
Adult Learning Theory ......................................................................................................... 25
iv
Informal Learning ................................................................................................................. 39
Mobile-Assisted Language Learning .................................................................................... 42
Technology Acceptance ........................................................................................................ 52
Chapter 3: Methodology ........................................................................................................... 60
Introduction ........................................................................................................................... 60
Research Questions ............................................................................................................... 60
Research Design.................................................................................................................... 60
Research Setting.................................................................................................................... 61
Instrumentation ..................................................................................................................... 64
Reliability and Validity ......................................................................................................... 68
Data Collection ..................................................................................................................... 69
Data Analysis ........................................................................................................................ 70
Ethical Considerations .......................................................................................................... 72
Summary ............................................................................................................................... 73
Chapter 4: Article for Publication ............................................................................................. 74
Abstract ................................................................................................................................. 74
Introduction ........................................................................................................................... 76
Literature Review and Theoretical Framework .................................................................... 77
Research Purpose and Questions .......................................................................................... 82
Methodology ......................................................................................................................... 83
Results and Discussion ......................................................................................................... 87
Conclusion .......................................................................................................................... 104
v
References ........................................................................................................................... 107
Chapter 5: Implications, Recommendations, Limitations, and Future Research .................... 116
Implications......................................................................................................................... 116
Recommendations ............................................................................................................... 118
Limitations .......................................................................................................................... 120
Future Research .................................................................................................................. 122
Conclusion .......................................................................................................................... 124
References ............................................................................................................................... 127
Appendix A: Survey instrument (English) ............................................................................. 156
Appendix B: Permission Letter............................................................................................... 162
Appendix C: Survey Instrument (Japanese) ........................................................................... 163
Appendix D: Cover Letter (Japanese)..................................................................................... 169
Appendix E: Cover Letter (English) ....................................................................................... 170
Appendix F: IRB Approval..................................................................................................... 171
vi
List of Tables
Table 1: Information Science English Classes by Skill and Semester.......................................... 63
Table 2: Original and Modified Scale Items ................................................................................. 65
Table 3: Overview of the Data Analysis Process.......................................................................... 70
Table 1 (Article): Means and Standard Deviations of Performance Expectancy (PE) ................. 88
Table 2 (Article): Means and Standard Deviations of Effort Expectancy (EE) ........................... 89
Table 3 (Article): Means and Standard Deviations of Lecturers’ Influence (LI) ......................... 90
Table 4 (Article): Means and Standard Deviations of Quality of Service (QoS) ......................... 91
Table 5 (Article): Means and Standard Deviations of Personal Innovativeness (PInn) ............... 92
Table 6 (Article): Means and Standard Deviations of Behavioral Intention (BI)......................... 93
Table 7 (Article): Means and Standard Deviations of Acceptance Scale and Subscale ............... 93
Table 8 (Article): Uses of Mobile Devices for Informal English-Language Learning................. 95
Table 9 (Article): Correlations Between Acceptance and Usage Scales ...................................... 96
Table 10 (Article): Number of Comments Coded as Identified Elements Representing Perceived
Advantages.................................................................................................................................. 101
Table 11 (Article): Number of Comments Coded as Identified Elements Representing Perceived
Disadvantages ............................................................................................................................. 103
vii
List of Figures
Figure 1: Research Model of M-learning Acceptance (Abu-Al-Aish & Love, 2013) .................. 56
viii
Chapter 1: Introduction to the Study
The ability to effectively communicate in English has become an essential skill for
workers in both private and public sector jobs throughout the world. According to the British
Council (Howson, 2013) there are over 1 billion people learning English as either a second or
foreign language. These individuals are learning the language in a variety of settings using
diversified methods of instruction or self-study. In recent years, the use of technology has
become central to the study of languages, providing students with greater access to educational
materials, authentic content, and tools to communicate with other language learners or native
speakers. In particular, mobile devices have become popular vehicles to facilitate language
learning due to their ubiquitous availability and flexibility (Viberg & Grönlund, 2012). While
mobile devices such as smartphones and tablets can be used in formal and non-formal learning
settings, they are especially useful for informal learning because they are so integrated into the
lives of users (Chen, 2013; Jones, Scanlon, & Clough, 2013; Kukulska-Hulme, 2010). In Japan,
the setting for this research study, mobile internet is more accessible than computer-based
internet, especially among marginalized groups in the society (Akiyoshi & Ono, 2008). For this
reason, they have been seen by many educators and researchers as ideal tools to facilitate
informal mobile-assisted language learning (MALL) for students of English as a foreign
language (EFL). It was the purpose of this research study to examine the acceptance and usage
of mobile technology for informal English-language learning in the Japanese higher education
context.
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Background
The English language is a required subject of study in the Japanese educational system.
Due to a policy change implemented in 2011, students receive their first exposure to the
language in primary school and continue until they graduate secondary school (Ministry of
Education Culture, Sports, Science, and Technology [MEXT, 2011a]). For students who
continue their education beyond the secondary level, English is often studied for an additional
two to four years. Furthermore, many students participate in nonformal study through so called
cram schools (juku) and English conversation schools (eikawa). However, standardized
measures of English language ability show that proficiency in the language is low among most
Japanese (Sakamoto, 2012). This is a concern for the Japanese government and corporations,
who see English ability as an essential skill for workers to compete in the increasingly globalized
world in which we live. For this reason, several policies to increase English proficiency have
been implemented. In primary and secondary school, the number of years that students study the
language has been increased (MEXT, 2008), and there has been an effort to employ more
communicative teaching methods instead of traditional teacher-centered instruction, which
previously focused on rote memorization of grammar and vocabulary (MEXT, 2011a). Japanese
companies are also making changes to aid in the development of English ability among their
employees. For example, several leading Japanese companies announced in 2010 that English
would be adopted as the official language of management-level personnel beginning in 2012, and
all other employees would be required to increase their English communication skills to meet
basic standards of proficiency (Asahi Shinbun, 2012). Furthermore, applicants with English
communicative competence or experience studying abroad would be given preference in the
2
hiring process. Yet, even though these reforms demonstrate a desire to increase English
proficiency in Japan, several of the root causes of the problem have been ignored.
Several factors have been identified as possible barriers to the development of English
proficiency among Japanese speakers. These challenges include flaws in the education system,
which places greater emphasis on passing scholastic entrance exams than developing
communicative skills (Kikuchi, 2013; Ryan, 2009; Yashima & Zenuk-Nishide, 2004) and a lack
of opportunities to interact in and be exposed to foreign languages. In addition, there are social
and cultural factors such as an aversion to making mistakes in order to save face and a propensity
towards modesty (Gudykunst & Kim, 2003) that may contribute to higher levels of foreignlanguage anxiety (FLA) and a decreased willingness to communicate (WTC) in the target
language (Matsuoka, 2008; Yashima & Zenuk-Nishide, 2004).
Considering these issues, computer-assisted language learning (CALL) may offer several
advantages to the Japanese learner of English. For example, Internet enabled ICT can provide
unlimited access to authentic content, learning resources, and communication opportunities in
the target language. Furthermore, because interaction can take place anonymously in many
cases, learners may be less inhibited and more likely to take risks, which may contribute to lower
levels of FLA and an increased WTC. Yet, unlike other developed countries, Japan has been
slow to adopt information and communication technologies (ICTs), especially in the field of
education (Aoki, 2010; Latchem, Jung, Aoki, & Ozkul, 2008). The exception to this is mobile
technology, especially mobile phones, which are ubiquitous in Japan, and are more accessible to
a number of disenfranchised groups within the country (Akiyoshi & Ono, 2008).
3
Mobile-Assisted Language Learning
MALL is a sub-field of CALL that has become the subject of a great deal of attention
from both researchers and educators in recent years. In Japan, mobile technologies are widely
available with over 94% of the population having access to one or more devices (Ministry of
Internal Affairs & Communication, 2014a). Mobile devices are affordable, portable, flexible,
and highly usable (Viberg & Grönlund, 2012). Due to these affordances, mobile technologies
are often seen as ideal tools to facilitate language learning in informal settings.
Research conducted by Barrs (2011) has shown that Japanese university students are
already using their smartphones for a number of language-learning purposes including taking
pictures of notes written by their teachers on whiteboards, listening to English language news
and podcasts, and using voice recognition applications to test pronunciation. However, research
conducted in Japanese university settings has also demonstrated that there is reluctance on the
part of some students to use their mobile devices for educational purposes due to privacy
concerns and a desire to separate their personal lives from educational endeavors (Kondo et al.,
2012; Stockwell, 2008, 2010). MALL may provide EFL students with an ideal platform in
which to engage in informal language learning, but in order for educators and researchers to
facilitate this practice, we must first seek to understand how students use and accept mobile
technology for this purpose.
Conceptual Framework
The conceptual framework that will be used in this study is the Technology Acceptance
Model (TAM). The TAM was designed to aid in the prediction of technology acceptance based
on the constructs of perceived usefulness, perceived ease of use, attitudes, and behavioral
4
intention. In the 30 years since the original model was developed, a large body of research has
been created which has resulted in the development of numerous variations of the original TAM.
While the TAM 2, TAM 3, and the Unified Theory of Acceptance and Use of Technology
(UTAT) function as general models, a number of technology-specific models have been
proposed for e-learning (Drennan, Kennedy, & Pisarski, 2005; Ma & Yuen, 2011), learning
management systems (Ngai, Poon, & Chan, 2007; Sánchez & Hueros, 2010), and mobile
learning (Abu-Al-Aish & Love, 2013; Park, Nam, & Cha, 2012).
Abu Al-Aishi and Love’s (2013) m-learning specific model has been modified and
translated into Japanese, with the permission of the researchers, to be used in this study of
informal MALL. The model developed by Abu Al-Aish and Love (2013) was based on the
UTAT and includes six constructs, which influence behavioral intention to use m-learning. The
constructs that directly affect behavioral intention are performance expectancy, effort
expectancy, social influence (lecturers), quality of service, and personal innovativeness while the
indirect influence was mobile device experience. A complete explanation of the model and
constructs can be found in Chapter 2.
Research Problem
In Japan, 98% of the population participate in six mandatory years of formal English
education (MEXT, 2011a); however, working proficiency of English among Japanese learners
remains low (Sakamoto, 2012). One limiting factor of formal education is that unless it is
delivered intensively in immersion programs, learners only come into contact with the target
language for a few hours each week. It is for this reason that language learners are often
encouraged to study abroad (Lys, 2013). However, through informal language learning activities
5
such as extensive reading and listening as well as communication with native or advanced
speakers of the target language, learners can greatly increase their exposure to the language they
are learning. Mobile devices, which are ubiquitous ICTs in Japan, can provide learners with
access to a wide range of authentic materials and native or near-native speaker interactions
without studying in a second language environment. Yet, few studies have been conducted in
the Japanese university context to explore the usage or acceptance of mobile devices for informal
English-language learning without researcher or instructor intervention. In order to make better
use of these technologies to provide learners with informal learning opportunities, it is important
to study how mobile technologies are currently used and the degree of acceptance towards them.
Purpose of This Study
The purpose of this study was to examine how and to what extent EFL students at a
private Japanese university were using their personal mobile devices to engage in informal
language learning. In addition, participants were surveyed regarding their acceptance of mobile
devices for the purpose of informal English-language learning. The results of this study will help
the researcher and others interested in EFL instruction and learning in the Japanese university
context to better understand the role that mobile devices play in informal language learning and
how acceptance and usage of the devices are related.
Research Questions
The following five research questions were addressed in this study:
1.
What is Japanese university students’ overall acceptance of the use of mobile devices
for informal English-language learning as measured by a quantitative scale based on
the TAM?
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2.
What is their actual use of mobile devices for informal English-language learning?
3.
What is the relationship between students’ acceptance of mobile devices for informal
English-language learning and their actual use?
4.
Are there any variations in responses based on individual differences?
5.
What do students perceive as potential advantages and disadvantages of mobile
devices for informal English-language learning?
Study Significance
Mobile devices such as smartphones, tablet computers, and MP3 players can provide
learners with inexpensive, flexible technology that can be used to facilitate informal language
learning (Kukulska-Hulme & Shield, 2008; Viberg & Grönlund, 2012). This is important in the
context of English-language learning in Japanese higher education because access to mobile
devices is ubiquitous among Japanese young adults (Stockwell, 2010), and English language
proficiency is becoming increasingly important for university graduates seeking employment.
While numerous research studies have examined the use of mobile devices in formal learning
environments in Japan (e.g., Stockwell, 2008, 2010; Thornton & Houser, 2005), only a few
studies have investigated the use of these devices in informal situations (e.g., Barrs, 2011; Ogata
et al., 2008). However, these informal learning studies often involved an intervention by the
researcher in the hopes of bridging formal and informal usage. The results of this study will
provide educators and researchers with valuable information regarding students’ usage and
acceptance of mobile devices in informal settings. The results of this study can be utilized to
improve the use of mobile devices in formal settings and to aid educators in encouraging and
facilitating informal learning among their students. Furthermore, the data that emerged from this
7
research will contribute to researchers’ understanding of informal MALL and may act as a
springboard for further research.
Methodology
Data was collected with the use of a paper-based questionnaire, which was distributed to
EFL students during class sessions by their course instructors. The questionnaires contained four
sections. The first section of the instrument contained a scale that measured participants’
acceptance of mobile devices for the purpose of language learning. The scale used for this
section of the questionnaire was developed by Abu Al-Aish and Love (2013) and adapted, with
permission, for this study. The second section consisted of a measurement of participants’
current usage of mobile devices for informal language study. This section was created by the
researcher based on his examination of the academic literature (Cheung & Hew, 2009; Patten,
Arnedillo-Sánchez, & Tangney, 2006; Santos & Ali, 2011) and his experience teaching EFL in
the Japanese university setting. The third section of the questionnaire consisted of several
demographics questions regarding the participants’ age, gender, academic major and standing,
nationality, and access to mobile devices. Two open-ended questions, which queried participants
on perceived advantages and disadvantages of the use of mobile devices for informal language
learning, made up the final section of the survey.
The researcher analyzed the data collected with these questionnaires quantitatively. First,
descriptive statistics were used to gauge the general level of acceptance and usage of personal
mobile devices for informal language study among the participants. Second, correlational
analysis was employed to examine the relationship between acceptance and usage of mobile
devices for this purpose. Next, variations in responses based on demographic factors such as
8
age, nationality, class standing, and major were investigated. Finally, students’ answers to openended questions regarding the advantages and disadvantages of using mobile devices for
informal English-language learning were analyzed using open-coding. Chapter 3 provides
additional information regarding the methodology of this study.
Researcher’s Role and Motivation
In recent years a number of initiatives have been launched by the MEXT in the hopes of
internationalizing higher education institutions in Japan for the dual purpose of attracting foreign
students to Japanese universities and preparing Japanese students to work in the globalized
marketplace. The university where the study took place, along with several other leading
Japanese universities, was selected by the MEXT in 2009 as a “Global 30 University” and in
2014 as a “Super Global University.” These designations carry with them an expectation that
selected universities will become “leading internationalization hubs” (Japan Society for the
Promotion of Science, 2011, para. 2) by increasing the number of courses taught in English,
including online classes, encouraging international exchange programs by partnering with
foreign institutions, and improving the English ability of university students.
For this reason, the university featured in this study is currently reevaluating the EFL
programs to seek new and better ways to engage students and develop their language
proficiency. The researcher, due to his position as both a lecturer at the university setting of this
study and a doctoral student in instructional technology at the University of Wyoming, has been
asked to contribute to the creation of a new curriculum and to aid in the development of
technology-based materials. In particular, the administration and senior faculty members would
like students to make use of their personal mobile devices for both formal and informal language
9
learning, as these devices are the primary ICTs used by students. This study is an essential first
step in this process, which will provide both faculty and administrators with an understanding of
the current use and acceptance of mobile technologies for language learning – vital information
which can greatly assist in the development of future course materials and EFL programs.
Definitions
English as a foreign language (EFL). The learning or teaching of the English language
in a culture or country where it is not the primary language of communication (i.e., a student
studying English in Japan) (Carter & Nunan, 2001).
English as a second language (ESL). The learning or teaching of the English language in
a culture or country where it is the primary language of communication (i.e., a student studying
English in the United States) (Carter & Nunan, 2001).
Computer-assisted language learning (CALL). The application of technology to the
teaching or learning of a foreign or second language (Stockwell, 2012a).
Personal mobile device. A hand-held computing device such as a smartphone or tablet
computer, which is owned by a student and can be used for the purpose of learning languages.
Mobile-assisted language learning (MALL). Language learning and teaching which
makes use of the portability of mobile technology in order to provide learners with specific
benefits (Kukulska-Hulme, 2013).
Informal learning. The process of learning that takes place outside of a formal classroom
without a teacher or prescribed curriculum (Laurillard, 2009). This learning can occur
incidentally without the learner’s conscious effort or through a program of self-directed study
(Stevens, 2010).
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Technology acceptance. The attitudes and perceptions of a user towards a particular
technology, which influences their decision to begin or continue using it (Davis, 1989).
Summary
In recent years mobile devices have developed into powerful ICTs that are being used for
a variety of purposes including language learning. These technologies are highly accessible to
Japanese university students but are mainly used as tools to facilitate personal communication
and entertainment. As Japanese universities endeavor to internationalize in order to increase
their competitiveness and prepare their students to meet the demands of today’s public and
private sector jobs, English-language skills have become increasingly important. However, most
solutions to this challenge have focused on improving formal learning programs. Informal
language learning, whether self-directed or incidental, can provide students with increased
exposure to the target language through learning materials, authentic content and opportunities to
interact with native or advanced speakers; however, little is known about how Japanese students
of EFL are using mobile technology for this purpose. Therefore, in this study, data was collected
by means of a survey instrument and analyzed quantitatively to determine the acceptance and
usage of mobile technology by Japanese university students for the purpose of language learning.
In addition, the relationship between acceptance and usage was explored. In Chapter 2, the
researcher provides a detailed account of the academic literature pertaining to informal MALL.
Both the theoretical and empirical literature will be addressed and will be presented in the
context of the Japanese university setting where the research took place. In Chapter 3, a detailed
description of the methodology used in this study is described including information regarding
the research setting and participants, the survey instrument, and the procedure. Chapter 4 of this
11
dissertation is a research article prepared by the research for the purpose of publication based on
the data collected in this study. In Chapter 5, the implications of the research study will be
discussed along with recommendations for how the results can be applied in practice. Finally,
the limitations of the current study will be presented and suggestions will be made for future
research.
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Chapter 2: Review of Literature
Introduction
This review of literature is an attempt not only to introduce the reader to research related
to the acceptance and use of informal mobile-assisted language learning (MALL) in higher
education, but also to frame that information in the Japanese context. This is important because
the setting of this study, a private Japanese university, presented unique opportunities and
challenges in regards to the implementation of technology in the English as a foreign language
(EFL) classroom. Of particular importance were Japanese cultural and social factors, which
affect both education and technology adoption in this country. Therefore, this review of
literature will begin with an introduction to the Japanese higher education system and the current
state of English education in the country. After this, theories of adult learning and second
language acquisition will be discussed in light of this context. Next, literature regarding informal
learning and MALL will be presented. Finally, technology acceptance will be explained and a
description of the models and constructs used in this study will be introduced.
The Japanese Educational Context – Policy, Practice, and Technology
Higher education in Japan. The Meiji Period (1868-1912) in Japanese history was a
time of dramatic change and modernization for the country. It was during this period, in 1872,
that Japan’s contemporary education system was created (Jansen, 1995). As part of this system,
universities were formed for each of the eight geographical regions by which the country was
divided (Okano & Tsuchiya, 1999). Since then, the number of higher education institutions has
grown to 1,243 (Ministry of Education, Culture, Sport, and Technology [MEXT], 2012), with 41
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universities internationally recognized by the Times Higher Education World University
Rankings for 2016.
Currently, the Japanese MEXT requires nine years of compulsory schooling. This
includes 6 years of primary school and three years of lower secondary school (MEXT, 2001).
However, the vast majority of Japanese young people (96%) go on to complete their high school
diploma (Jones, 2011). Furthermore, 40.4% of Japanese people earn their university degrees
(Economic Intelligence Unit, 2014).
There are three types of institutions in the Japanese higher education system – junior
colleges, technical colleges, and universities (MEXT, 2012). Surprisingly, over 70% of Japanese
universities are private; yet, the MEXT maintains a strong influence on both private and public
institutions (Nomura & Abe, 2010). In most cases, admission to a university in Japan is based on
the results of stringent entrance examinations. Because graduating from a good university is
important to obtain a position at a top company, high school students spend a tremendous
amount of time studying for these examinations, and many are enrolled in private cram schools
in order to increase their chances for success (Jones, 2011). Despite the effort students exert to
gain entrance into a good university, most institutes of higher education in Japan are not very
academically rigorous once students are accepted (Hayes, 1997).
In recent years, Japanese higher education has faced a number of challenges. According
to Nomura and Abe (2010) some of these issues include “pressures to respond to shrinking
student populations, to compete in the globalized higher education markets, and to meet various
social demands” (p. 121). One solution that the MEXT (2012) identified as an answer to these
challenges is for Japanese universities to become more international. For this reason, several
14
goals are being pursued, including increasing participation in study abroad programs and
attracting international students to study at Japanese institutions through the availability of
scholarships and the opportunity to take classes in English. However, English-language
proficiency may present a challenge to the implementation of these programs in Japan, where
despite years of formal schooling in the subject, practical competence remains low.
English education in Japan. English is a required subject in the Japanese educational
system where 98% of the population studies the language for at least 6 years (MEXT, 2011a).
For the Japanese people who participate in higher education, an additional two to four years of
English classes are often required. However, few Japanese learners of English achieve practical
competence in the language (Sakamoto, 2012). The Test of English as a Foreign Language
(TOEFL) is a standardized assessment of English proficiency used around the world. The most
recent results of the TOEFL ranked Japan 31st among 35 Asian countries (Educational Testing
Service [ETS], 2014). In fact, the only Asian countries whose scores were lower on the TOEFL
for that year were Cambodia, The People’s Democratic Republic of Lao, Timor-Leste, and
Tajikistan, all developing nations. An alternative assessment, the Education First English
Proficiency Index (EF EPI), is more optimistic in its rankings and classified Japanese adult
English proficiency as moderate (EF EPI, 2015). Furthermore, the EF EPI, which uses two tests
to assess proficiency, found that the English proficiency of women was superior to men, and city
dwellers were more skilled than those in rural areas. However, scores have not improved in the
past 7 years. Because English has emerged as a lingua franca for international communication
(Jenkins, 2014), limitations in proficiency can have an impact on Japan’s ability to participate in
both the globalized marketplace and political arena.
15
Over the years, the government has proposed a number of policies to improve the English
fluency of Japanese people. In 2000, then Prime Minister Keizō Obuchi set a goal for English to
become an official language. However, Obuchi’s death in May of 2000, as well as public
opposition to the policy, prevented it from being implemented (Hashimoto, 2009). In 2002, the
MEXT released documents promoting the “cultivation of Japanese with English abilities” (para.
23). In these documents, a 5-year plan of action to develop working proficiency in the language
upon completion of formal schooling on the subject was put forth. Further changes to the
curriculum were made in 2008 when English education began to be introduced at the primary
school level. In 2011, the MEXT called for additional focus on the development of
communicative language abilities stating “classes must be shifted from lecture style toward
student-centered language activities by employing such educational forms as speeches,
presentations, debates and discussions” (MEXT, 2011a, p. 3). However, the results of the
TOEFL and EF EPI seem to suggest that these policies have done little to improve the English
abilities of the average Japanese person.
A number of reasons have been cited as to why the Japanese public has failed to achieve
working proficiency in English despite years of formal study. One barrier stems from a fear that
internationalization will lead to the erosion of Japanese culture and traditions (Hashimoto, 2009).
In addition, the structure of the educational system, particularly the priority placed on preparing
students for rigorous entrance examinations, has been identified as another barrier (Yashima &
Zenuk-Nishide, 2004). These examinations focus on grammar and vocabulary knowledge rather
than the development of communicative competence or comprehension of authentic materials.
For this reason, Japanese students spend a considerable amount of time engaged in memorization
16
of these components of the language rather than their application. Finally, certain Japanese
cultural and social factors may present challenges to effective language acquisition. While not a
panacea, technology offer several benefits to language learners including unlimited access to
authentic content and learning materials, opportunities for communication with native or nearnative speakers of the target language, and the possibility to interact with others in an anonymous
environment.
Technology in Japanese higher education. Japan is known throughout the world as a
highly technical nation. However, Japan has been slower to adopt educational technology than
other developed nations (Aoki, 2010; Latchem et al., 2008). A report from the MEXT (2011b)
concluded that while the Japanese educational system has been effective in developing numeracy
and literacy skills among its students, several 21st century literacies have been neglected. This
includes digital literacy as well as information-seeking skills. Therefore, the MEXT has
proposed a plan to increase students’ skills in these critical areas through the use of information
and communication technology (ICT) (MEXT, 2011b). However, this is not the first proposal by
the Japanese government to increase the use and knowledge of ICT in education.
From the 2002/2003 academic year, the MEXT began to require all junior and senior
high school students to complete information studies courses as part of their graduation
requirements. Yet, many university educators are surprised to find that their students do not
possess the basic computer literacy skills necessary to participate in higher education classes
(Murray & Blyth, 2011). A study conducted by Lockley (2011) found that 11% of new
university entrants had never participated in any ICT training during their time at high school
despite these courses being mandatory. Of those who had received training, many could not
17
remember how to use such programs as PowerPoint, Excel, and Word upon entering university.
A similar study conducted by Murray and Blyth (2011) confirmed the findings of Lockley
(2011), and worryingly showed that even with up to 8 years of experience with information and
communication technologies (ICTs), Japanese students did not have experience with software
that would be critical for their future employment such as word-processing, spreadsheet, and
presentation software. Most disconcerting was the discovery that 55% of students surveyed
indicated they had ‘never’ or ‘almost never’ used word-processing software.
In contrast to the sluggish adoption of most ICTs, mobile technology is widely used in
Japan for both professional and personal reasons, and is used more often than in other developed
countries to access the Internet (Akiyoshi & Ono, 2008). Computer-based Internet adoption in
Japan was hampered by high costs, a lack of English proficiency, and poor keyboarding skills.
However, the introduction of i-mode (Internet mode) by the Japanese mobile service provider
NTT DoCoMo in 1999 offered an alternative to computer-based Internet access that addressed
many of these barriers to adoption (Akiyoshi & Ono, 2008). In addition to providing a lower
cost alternative to access the Internet than computers, NTT DoCoMo was successful in inviting
Japanese companies to develop i-mode content and service in Japanese (Akiyoshi & Ono, 2008).
For these reasons, the mobile phone in Japan has become as common as the computer as a way
to access the Internet, even before the introduction of smartphones (Akiyoshi & Ono, 2008; Ono
& Zavodny, 2007).
Second Language Acquisition
Second language acquisition (SLA) is an interdisciplinary field of study encompassing
aspects of linguistics, cross-cultural communication, and pedagogy (Gass & Selinker, 2008).
18
While early research in SLA concentrated on behavioristic approaches to learning, in the past
few decades there has been a shift to better understand the process in which languages are
acquired from the learner’s perspective. In doing so, researchers have endeavored to identify the
factors that contribute to language acquisition and form theories in an effort to explain this
complicated phenomenon.
Input, output, and interaction. Fundamental to the study of SLA is the role that
language input, output, and interaction play in the learning process. Input in SLA refers to
passive language processes such as reading and listening resulting in comprehension by the
learner. However, there is an important distinction between input and intake of information
(Corder, 1967). Input is all the available information presented to a learner while intake is the
portion of that information which is comprehensible. Krashen (1981, 1985, 1992) proposed one
of the most well-known, albeit controversial, SLA theories dealing with input. This model is
commonly known as Krashen’s Input Hypothesis, and is composed of five parts: (1) AcquisitionLearning Hypothesis, (2) Monitor Hypothesis, (3) Natural Order Hypothesis, (4) Input
Hypothesis, and (5) Affective Filter Hypothesis.
In the Acquisition-Learning Hypothesis Krashen posits that the second language (L2),
like the first language (L1), is acquired through meaningful communication in naturalistic
settings. This hypothesis sees acquisition as a different process from language learning, where
students focus on linguistic form and rules. The Monitor Hypothesis refers to the process by
which learners, when given sufficient time, can apply learned linguistic rules to target language
output. The Natural Order Hypothesis is the assertion that linguistic forms are acquired in a
specific order, which cannot be circumvented through instruction. The Input Hypothesis is
19
central to Krashen’s view of SLA and argues that comprehensible input is both necessary and
sufficient for the language acquisition process. Comprehensible input is defined as L2 input
slightly above the current level of knowledge of the learner (i + 1). Output, speaking and
writing, is not seen as a component of the acquisition process, but rather as an inevitable result of
sufficient comprehensible input being provided to the learner. Finally, the Affective-Filter
Hypothesis suggests that input can be prevented from becoming intake due the presence or lack
of various affective factors including motivation, self-confidence, or anxiety.
Krashen’s claims, while influential in the field of SLA, have been criticized by a number
of researchers. Gregg (1984), for example, has argued that Krashen provided no evidence to
support his assertion of the separation between conscious (learned) and unconscious (acquired)
language knowledge. According to Gass and Selinker (2008), the Acquisition-Learning
Hypothesis is counterintuitive in this regard and, without adequate evidence, provides little
opportunity to test the validity of this claim. In addition, some research has shown both explicit
and implicit learning play important and distinct roles in SLA. The Natural Order Hypothesis
has some support in morpheme order studies; however, Krashen’s hypothesis disregards both the
role L1 transfer may play in the process, and the natural variation that occurs in L2 acquisition
(Mitchell, Myles, & Marsden, 2013). Long (2015) argued that analytical approaches, such as
Krashen’s, suffer from four problems. First, too much faith is put in adult learners’ capacity to
learn languages implicitly. Second, implicit learning is time consuming, and therefore, not as
efficient as other approaches. Third, adult learners need both positive and negative evidence to
acquire an L2; the latter is lacking in the Natural approach. Finally, analytical approaches do not
make use of teacher interventions, which bring attention to language features in addition to
20
simple exposure to the L2. While researchers agree that meaningful input is essential for
successful language acquisition, many disagree with Krashen’s claim that input is the only
necessary component.
According to Nation (2007) there are four-strands of language-learning activities that
should be given equal treatment in a well-designed program. These strands include meaningfocused input, meaning-focused output, language focused learning, and fluency development.
Of these four, the importance of output in language acquisition was highlighted by Swain’s
(Swain, 1985, 1995, 2005) reaction to Krashen’s Input Hypothesis. The Output Hypothesis was
developed by Swain (1995, 1985) based on her experience studying L2 French learners in an
immersion environment in Canada (Mitchell et al., 2013). The output hypothesis claims that
output provides several unique benefits to the language learner including (a) noticing/triggering,
(b) hypothesis testing, and (c) reflection. The noticing/triggering function of output is when
learners realize a lack of linguistic knowledge of the L2 when trying to produce output.
According to Izumi (2002), this occurs more readily among learners when producing output than
when they are receiving input. Hypothesis testing is the process by which a learner tries new
forms in the L2 to determine if they are correct or not. Feedback serves as a gauge for the
learner, which guides him or her to maintain or modify these forms (Nation, 2007). Finally, the
metalinguistic (reflective) function of output takes place when language learners work with
others in problem solving activities centered on language.
The importance of interaction with other interlocutors in SLA has been highlighted in
research by Long (1981, 1983a, 1983b). This position, based in social constructivism, sees
modified interaction, whereby native and advanced speakers of a language use strategies to make
21
their input more comprehensible to language learners, as important to SLA. These strategies
might include clarification requests and confirmation checks. While Long’s Interaction
Hypothesis initially proposed a link between interaction and comprehensible input, later
modifications (Long, 1996) hypothesized that interaction might have an effect on L2 acquisition.
Mackey (1999) provided strong evidence for the positive effects of interaction. However, a
review of experimental studies by Keck, Iberri-Shea, Tracy-Ventura, and Wa-Mbaleka (2006)
showed only short term gains (unto 29 days). Mackey and Goo’s (2007) meta-analysis
demonstrated evidence for longer term effects, but only for participants’ acquisition of grammar.
In the Japanese context an important consideration is the fact that English is studied as a
foreign language rather than a second language. For this reason, students have little chance to
come into contact with the language outside of the classroom (Chen, 2001; Cheng, 1998) and do
not commonly use the language in their daily lives (Tse, 1995). ICTs can provide students’ with
“additional social and interactive contexts for L2 learning” (Loewen, 2015, p. 152); however,
access to these devices can be limited. Mobile technologies, due to their high rate of penetration
among Japanese university students, low cost, and flexibility can provide students with the
necessary language content to facilitate successful acquisition.
The good language learner. There are some individuals that seem to acquire languages
effortlessly, while others struggle through every stage of the process. Researchers and educators
have long pondered why this is so. Do good language learners have some sort of innate aptitude
for language learning, or are they just employing strategies that can be learned and utilized by
anyone? During the 1970s, several researchers (Cohen, 1977; Rubin, 1975; Naiman, Fröhlich,
Stern, & Tedesco, 1978), endeavored to find the answer to this question by studying the traits
22
and practices of good language learners. These studies showed that there were a number of
strategies employed by good language learners that could be utilized by anyone studying a
foreign or second language. Based on a study conducted by Naiman et al. (1978), the
researchers concluded that adult language learners who were successful employed 5 strategies.
These strategies included: (a) being active in the learning process, (b) noticing the patterns of the
language being studied, (c) using the target language to try to communicate, (d) managing
affective issues, and (e) monitoring individual progress. In 1982, Rubin and Thompson proposed
14 characteristics of the good language learner that included autonomy, tolerance of ambiguity,
and the use of communicative and learning strategies. Investigations regarding the role of
individual differences continue to be a subject of interest to researchers in the field of SLA;
however, these factors are seen to be less predictive of language learning success than once
imagined (Dörnyei & Ryan, 2015).
One learner characteristic, which is still given considerable attention in the literature, is
motivation. Ellis (2004) defines motivation as the effort that a language learner applies to his or
her study of an L2 as a result of his or her perceived need or desires to accomplish the task of
acquisition. According to Oroujlou and Vahedi (2011), motivation is an important factor in
driving individuals to begin the study of a language, and imperative in sustaining the practice for
the long periods of time required to be successful at its acquisition.
Several models have been developed that explain the role that motivation plays in the
SLA process. Gardner and Lambert (1972) proposed that motivation to study a language could
be classified as either instrumental or integrative. An instrumental orientation refers to motives
related to career or academic success, while integrative orientation is characterized by cultural
23
and social goals. A large body of research has concentrated on which orientation leads to better
outcomes in SLA; however, results have been mixed. This may be because these factors cannot
be studied in isolation. Research by Dörnyei (1994, 2001) has looked at how the learning
context can affect motivation in SLA acquisition. More recently, Dörnyei and Ushioda (2011)
have endeavored to place motivation as part of a “complex dynamic system” that makes up the
L2 learning process (Mitchell, Myles, & Mardsen, 2013, p. 23).
Although these characteristics and strategies are a helpful guideline for students and
teachers, early research into the good language learner ignored a slew of additional factors that
could affect the ease and speed of SLA. Most importantly, according to Norton and Toohey
(2001), the role of the social context, which Larsen-Freeman and Cameron (2008, p. 126) view
as “indispensible” for language learning, did not receive sufficient attention in early studies. In
their research, Norton and Toohey (2001) recognized that human agency played an important
role in contributing to successful SLA, but they warned that these practices must be viewed in
light of the social context of the learner. The idea that social context is imperative to a complete
understanding of SLA can be found in the sociocognitive approach. According to Atkinson
(2011), the sociocognitive approach operates on the premise that “mind, body, and world
function integratively in second language acquisition” (p. 143). Three important implications
stem from this understanding. First, learning is a natural phenomenon that occurs at all times
and in all places. Second, cognition can be supported by tools, which exist in the world
including technology. And finally, that language is best learned when the learner is placed in
situations and environments where use of the language is necessary to accomplish social goals.
24
Practical research utilizing the sociocognitive framework has produced promising results
in the field of SLA. Hondo (2013) found that Japanese EFL learners benefited when learning
tasks were designed to include both cognitive and social elements. De Costa (2014) also showed
how a sociocognitive approach to the study of willingness to communicate in English as a lingua
franca could be beneficial to researchers and inform teaching practice in the ESL/EFL classroom.
Adult Learning Theory
Several theories of adult learning can be applied to the practice of informal MALL.
These theories describe the ways in which adult learners absorb new knowledge and how it is
processed and retained. Like SLA, the focus of research in adult learning theories has shifted
from approaches grounded in behaviorism to frameworks that consider individual cognition and
constructivism. For the purpose of this research study andragogy, constructivism, and social
learning theory will be explored.
Andragogy. Andragogy, the theory and practice of adult education, was first introduced
to the United States from Europe by Malcolm Knowles in 1968 (Merriam, Caffarella, &
Baumgartner, 2007; Rachal, 2002; Taylor & Kroth, 2009). Since that time, it has become one of
the best-known paradigms for understanding how adults learn (Merriam et al., 2007).
Andragogy was first seen to be dichotomous to pedagogy (Blondy, 2007; Taylor & Kroth, 2009),
but over time, Knowles began to view pedagogy and andragogy as lying at opposite ends of a
continuum (Blondy, 2007). Therefore, pedagogy represented teacher-centered instructional
practices, while andragogy was characterized by its focus on the learner (Yoshimoto, 2007).
Andragogy is based on six assumptions that characterize adult learners. Adult learners: (a) are
self-directed, (b) possess prior experience that influences the learning process, (c) are
25
characterized by their readiness to learn, (e) are usually learning to address an immediate
concern, (f) are internally rather than externally motivated, and (g) want to know why they are
learning something (Knowles, 1980, 1984).
These assumptions guide the educator in facilitating instruction for students who are
motivated and ready to take charge of their own learning. Therefore, learners are respected for
their knowledge, and curriculum is often negotiated rather than imposed (Chan, 2010).
Although educators in many settings utilize the principles of andragogy in their practice (Blondy,
2007), there are several criticisms of the paradigm (Merriam et al., 2007; Rachal, 2002; Taylor &
Kroth, 2009). These criticisms include debates regarding the identification of andragogy as a
theory rather than a set of principles or guidelines for best practice (Davenport & Davenport,
1985), the lack of consideration andragogy gives to the social and cultural context of the learner
(Pratt, 1991), and a limited amount of empirical research supporting andragogy claims (Rachal,
2002).
Empirical support for the theory of andragogy has been sparse (Merriam et al., 2007;
Rachal, 2002). Several of the studies where researchers have made an attempt to test its
hypotheses are contained in what Rachal (2002) refers to as “unread dissertations” (p. 212) and a
handful of peer-reviewed articles from the 1980s and 1990s. However, the reason for this may
be found in the difficulty in assessing outcomes in settings utilizing andragogy, because
Knowles, according to Rachal (2002), did not view grades and traditional tests as true measures
of adult learning. However, studies that have examined how andragogical principles are applied
to real-world settings and look beyond traditional assessment methods to gauge the results, paint
a brighter view of the importance of this theory in adult learning. An example of such research
26
can be found in a study by Birzer (2003), which investigated the use of andragogy in police
training. According to the author, traditional police training commonly utilizes behavioristic
models of teaching; yet, andragogy, with its focus on learner-centered instruction might be more
beneficial. Birzer (2003) found that when police officers underwent training grounded in the
principles of andragogy they were more self-directed and proactive and had better problemsolving skills when working in their communities.
Forrest and Peterson (2006) found andragogy to be beneficial to the study of
management. The authors asserted that andragogy is essential for preparing students in this field
to deal with the practical problems they will face in their future jobs. This is because andragogy
focuses on student-centered learning and the application of theoretical understanding.
These examples demonstrate that the use of andragogical principles in teaching and
learning can produce favorable results in a variety of fields when outcomes are measured in nontraditional ways. Andragogy may not be supported by copious empirical evidence, but the
practical experience of educators has shown andragogical principles as beneficial to students
(Merriam et al., 2007). However, andragogy has also been criticized for the lack of attention it
gives to social and cultural factors (Pratt, 1991). Therefore, we must examine how these
assumptions apply to the particular context of Japanese university students.
Japan is a very homogeneous society with ethnic Japanese making up 98.4% of the
population (Ministry of Internal Affairs and Communication, 2014b). For this reason, the
Japanese have been able to retain many traditional aspects of their culture whose effects may
have been reduced or even eliminated in a more diverse society. The student population in
Japanese universities is predominantly between the ages of 18 and 22, and come from very
27
similar family and educational backgrounds (Fuwa, 2009). These students have attended public
or private elementary, junior and senior high schools where the curriculum is highly regulated by
the MEXT (Nomura & Abe, 2010).
Instruction in Japan, like in most East Asian cultures, focuses on teacher-centered lecture,
memorization, and drill and practice (Littrell, 2006). While the Japanese educational system
ranks high in comparison to other nations in terms of student literacy and math skills (Economic
Intelligence Unit, 2014) graduates of this system tend to be poor in their ability to seek
information independently and to apply and interpret this information without the help of an
instructor (MEXT, 2011b). This reliance on the teacher as the source of knowledge for Japanese
students may be rooted in the influence of Confucianism, which accepts hierarchical
relationships and promotes respect for individuals in higher power positions (Carless, 2012).
According to Davies and Ikeno (2002), Japanese students still believe that “teachers should be
respected because of their age, experience and ability and what teachers say is always considered
right” (p. 191). For this reason, several of Knowles’s (1980, 1984) assumptions such as learner
self-direction, readiness, and motivation may not accurately characterize Japanese university
students.
In addition, Knowles’s (1980) assumption that adult learners are addressing an immediate
need through their study may not be applicable in the Japanese university context. Japanese
learners studying EFL in the university setting are often doing so to meet graduation
requirements. While many large Japanese companies are making English the primary language
of business communication (Asahi Shinbun, 2012), for university students in their first few years
of study, graduation and job hunting can seem like a distant goal.
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Finally, Knowles (1984) suggests that adult learners tend to be internally rather than
externally motivated. Internal motivation, also called intrinsic motivation, refers to learning for
enjoyment rather than for an outside reward (Brown, 2007). Research has shown that both
internal and external motivation can positively influence outcomes in foreign/second language
learning (Chang, 2005); however, students who are more internally motivated have demonstrated
greater persistence in learning (Levesque, Zuehlke, Stanek, & Ryan, 2004; Noels, Pelletier,
Clement, & Vallerand, 2000) and higher GPA attainment (O’Reilly, 2014). While there
certainly are Japanese students who are internally motivated to study English, external
motivators such as earning academic credit, finding a good job, and passing examinations are
also present.
Merriam et al. (2007) summarized the limitations as well as the place of andragogy in
adult learning by stating, “[Andragogy] does not give us the total picture, nor is it a panacea for
fixing adult learning practices. Rather, it constitutes one piece of the rich mosaic of adult
learning” (p. 92). For this reason it is important to consider additional theories of learning that
can add to or support the framework which andragogy provides. Two such theories are
constructivism and social learning theory.
Constructivism. Constructivism is a poststructuralist philosophy most closely associated
with the works of Jean Piaget and Lev Vygotsky (Brown, 2007). Constructivism is commonly
divided into two forms – cognitive and social. Cognitive constructivism, based on the work of
Piaget, emphasizes the individual’s ability to construct knowledge based on their perceptions of
reality (Bodner, 1986). Due to the emphasis placed on the individual, learning is seen as an
active process where learners play a central role (Slavin, 2003). While cognitive constructivism
29
acknowledges several unique aspects of the adult learner such as self-directedness, experience,
and motivation, there is still a lack of focus on social factors and cultural context.
Social constructivism, as promoted by Vygotsky (1978), posits that knowledge is
constructed through interaction, collaboration, and cooperation with others rather than in
isolation. Therefore, social as well as cultural contexts are viewed as vital components in this
epistemology (Brown, 2007). Several important concepts for understanding and implementing
social constructivism in learning and teaching have been provided in Vygotsky’s social
development theory. One such concept is the Zone of Proximal Development (ZPD), which
Brown (2007) defined as the “the distance between learners’ existing developmental state and
their potential development” (p. 13). In this view, the learner is dependent on interaction
between him or herself and what Vygotsky calls a More Knowledgeable Other (MKO) who
provides scaffolding to the learner to bridge the gap between their current level knowledge and
the knowledge they wish to attain (Abdullah, Hussin, Asra, & Zakaria, 2013).
Constructivism is the basis of many theories of adult learning (Merriam et al., 2007). The
application of constructivism in teaching is characterized by learner-centered, flexible, and
interactive activities (Johnson, 2009). However, constructivism, like andragogy, has been
criticized by some researchers due to a lack of empirical evidence. According to Johnson
(2009), criticisms of the effectiveness of constructivism are rooted in methods of inquiry that
seek to measure outcomes objectively through methods like standardized tests. However,
constructivist education practices prefer to measure student achievement through more subjective
criteria such as the experience of learners (Morrow, 1992).
30
Research that focuses on these subjective experiences rather than objectively measured
outcomes shows a number of benefits to a constructivist approach to teaching and learning. An
example of such empirical research can be found in a unique approach to assessment employed
by Duncan and Buskirk-Cohen (2011). In their study, Duncan and Buskirk-Cohen (2011)
employed a student-centered assessment approach, which simply asked students to demonstrate
the knowledge they had acquired after participating in a university level course on education or
psychology by creating their own assessment. The researchers found that students were able to
apply knowledge in new and innovative ways in their self-assessments and demonstrated deep
learning. In addition, both the students and instructors found the experience more enjoyable than
traditional assessments.
Another research study examined the effects of a student-centered approach in a thirdyear pharmacology program (Cheang, 2009). The researcher replaced teacher-centered lecture
with student-centered discovery learning where students were given hypothetical case studies
and worked in small groups to create and present solutions to the class. Participants were
administered the Motivated Strategies for Learning Questionnaire before and after the semester.
The results of this study showed that constructivist based teaching methods increased students’
intrinsic motivation, self-efficacy, critical thinking, and metacognitive self-regulation.
According to Comas-Quinn, Mardomingo, and Valentine (2009), mobile learning (ML) is
closely associated with the theory of constructivism and the related concepts of learnercenteredness and situated-learning. In addition, constructivist instructional strategies have
become the primary framework for facilitating second/foreign language instruction in this
century (Brown, 2007).
31
From a social constructivist perspective, which identifies sharing and interaction as a vital
component of knowledge creation, mobile devices provide an ideal platform for the facilitation
of such activities (Comas-Quinn et al., 2009). Interaction and sharing have an impact on secondlanguage acquisition as well, where these have been shown to aid in meaning negotiation and can
lead to increases in target language output (Foster & Ohta, 2005).
Furthermore, the concept of ZPD, while usually applied to face-to-face instruction, can
also be facilitated by computer software which can serve as the MKO (Abdullah, Hussin, Asra,
& Zakaria, 2013). By using a mobile device a student can access software in the form of
applications as well as authentic materials and cultural information. A study by Ducate and
Lomicka (2013) found that access to an iPod Touch increased students’ ability to interact with
authentic materials and experience target language culture while participating in autonomous
language learning. Furthermore, because mobile devices provide students with access to
resources such as dictionaries or online forums and serve as a means to communicate with
teachers and peers, instructional scaffolding is easily accessible to students to make sense of the
authentic material with which they interact (Vavoula, Sharples, Scanlon, Lonsdale, & Jones,
2005).
In addition to considering the use of constructivism in m-learning we must also
acknowledge the role that culture may play in applying this theory in the Japanese context.
While Japanese education tends to focus on teacher-centered lecture as the primary form of
instruction, the results of several research studies have shown that Asian students from
collectivist cultures prefer group work more than students from individualistic countries such as
the United States and Australia (Chuang, 2011). According to Hofstede, Hofstede, and Minikov
32
(2010), members of individualistic and collectivist societies can be distinguished by whether
their thoughts and actions reflect a concern for their self and immediate family or for the larger
groups to which they belong. The Japanese culture is highly collective, possibly because of a
long tradition of rice farming, which requires cooperation between members of a community
(Davies & Ikeno, 2002).
Although collectivism has a positive effect on preference for group work and social
interaction in learning situations, collectivist societies tend to favor conformity, which can
hamper the free exchange of ideas and opinions that might be socially disruptive (Littrell, 2006).
This propensity towards conformity is epitomized in the Japanese proverb deru kui wa utareru
(the nail that sticks out is hammered in). When a student communicates freely or volunteers to
answer questions in a class, this can be seen as an attempt by that individual to stand out from his
or her peers (Davies & Ikeno, 2002). Therefore, Japanese people are taught from a young age to
be modest (kenson) and to hold back (enryo) in order to avoid individualistic behavior.
Finally, uncertainty avoidance, which is characterized by feelings of unease associated
with unpredictable situations (Hofstede et al., 2010), can also impede the implementation of
constructivism in Japanese education. According to Hofstede’s Uncertainty Avoidance Index
(UAI), Japan has the 7th highest score on this construct, 92, when compared to the other nations
examined. This may not be surprising when one realizes that Japan has a long history of
enforcing etiquette and formal rules of behavior, which if violated, at least historically, could
have cost an individual his or her life. In order to avoid such consequences, the Japanese, over
the last two thousand years, have developed a preference for constancy, which can be seen in
their practice of kata. Kata can be defined as a formalized pattern for performing an action and
33
is most often associated with the pre-arranged patterns of movements practiced in martial arts.
However, in Japan, kata can also be seen in such mundane daily activities as the way one eats or
sits. De Mente (1997) described the practice of kata in feudal Japan as follows:
There was only one correct way to perform each of these actions. Deviations were not
allowed because everyone was conditioned to follow the same etiquette in their personal
behavior and the same form and process in their particular work. The overall behavior of
the Japanese became homogenized to a degree seldom seen in other societies (p. 17).
Because constructivist educational practices tend to give the learner a central and active
role in their learning, both teachers and students in Japan may feel unease with the dynamic and
unstructured learning environment that this creates (Hsu, 2013). Escandon (2002) suggested that
while constructivist methods of instruction predominate language-teaching practices in most
countries, the tendency for Japanese education to utilize teacher-centered methods and the fact
that constructivist practices can sometimes contradict Japanese socialization goals, such as
modesty, conformity, and respect for authority, might make it difficult to apply in this context.
Despite these barriers to the use of constructivist approaches in education in Japan, there is
evidence that individuals from Confucian heritage cultures can adjust their learning preferences
based on their environment (Chuang, 2011). This suggests that learners have a degree of control
over their environment, a key concept in Bandura’s (1977) social cognitive theory.
Social learning/cognitive theory. Social Learning Theory, which later became known
as Social Cognitive Theory and is based on the work of Albert Bandura (1977a, 1986),
emphasizes the social environment and asserts that learning can take place through observation
(Merriam et al., 2007). While earlier models of social learning were put forth by Miller and
34
Dollard (1941) and Rotter (1954), Bandura’s (1977a, 1986) social cognitive model has been the
most enduring and is based on a number of assumptions including triadic reciprocity, agency,
and vicarious learning.
Triadic reciprocity, or triadic determinism, refers to the relationship between personal,
environmental, and behavioral factors that influence the learning process. Bandura (2001)
asserted that these factors interacted dynamically and bi-directionally. This acknowledgment of
the role of the individual lay in contrast to behaviorist theories, which saw the learner’s
environment as fixed and predictive of behavior (Merriam et al., 2007).
In social cognitive theory, learners possess the agency to affect both their environment
and behavior (Bandura, 2001). Bandura (1989) described the individual in triadic reciprocity as
“neither autonomous agents nor simply mechanical conveyers of animating environmental
influences” (p. 1175). Instead the personal contributions of learners, both active and incidental,
have an effect on the other factors of the triad. Due to this increased agency, factors such as
outcome expectations, goal setting, self-efficacy and self-regulation are hypothesized to play
important roles in the learning process (Bandura, 1989).
Finally, a key component of social cognitive theory is that learning can take place
vicariously through observation (Merriam et al., 2007). Vicarious learning refers to the ability to
model behavior without taking part in the observed action (Bandura, 2001). Attention, memory,
procedure, and motivation are the sub-processes of observational learning (Merriam et al., 2007).
Social cognitive theory has a long history of empirical studies based on its assumptions.
Probably the most researched components of social cognitive theory are the role of self-efficacy
and self-regulation on behavior. Research on these factors has been conducted in a variety of
35
fields including health (Bandura, 2005), technology acceptance (Park et al., 2012; Teo & Zhou,
2014), and education (Komarraju & Nadler, 2013; Ning & Downing, 2012).
Self-efficacy is a learner’s belief that she or he can accomplish a goal given a specific set
of circumstances (Bandura, 1986). The concept is related to but not the same as self-esteem and
self-confidence, which are associated “with a more holistic view of one’s capabilities” (Straub,
2009, p. 629). Self-efficacy is a key determinant of performance and, in some cases, may be
more predictive of outcomes than actual ability (Bandura, 1977b). Research shows that selfefficacy can be improved upon (Bandura, 1989) and that individuals with high levels of selfefficacy and confidence are more likely to believe they have the power to change intelligence
(Komarraju & Nadler, 2013). These students are also more likely to set and pursue both mastery
and performance goals (Komarraju & Nadler, 2013). Self-efficacy can be augmented when
learners self-regulate both internally and externally, follow a schedule of study, and actively seek
help when needed (Pintrich, 2004).
Self-regulation is the ability of learner to control his or her behavior in order to achieve a
goal (Shirkhani & Ghaemi, 2011). An individual, for example, who is studying for a test may set
a goal to study for one hour every day. By maintaining this schedule until the goal is achieved
she or he demonstrates her or his propensity to self-regulate behavior. Self-regulation has also
been shown, along with motivation, to act as a mediator between the factors of learning
experience and academic performance (Ning & Downing, 2012). Therefore, efforts to improve
the learning experience can affect self-regulation directly and academic performance indirectly
(Ning & Downing, 2012).
36
Finally, validation of observational learning was first established through a study
commonly referred to as the Bobo Doll experiment (Bandura, Ross, & Ross, 1961). In this
experiment, children were separated into two experimental groups and a control group. The
experiment consisted of three stages. In the first stage, the experimental group observed an adult
displaying physical aggression towards a large inflatable doll (Bobo doll), while the adult model
in the second experimental group did not display aggressive behavior. The children in the
control group were not exposed to any adult model. In the second stage, another experimental
group of children experienced a mild aggression arousal when they were told they could play
with a set of toys and then were informed that they could not use the toys because they were for
other children. Finally, the children in both experimental groups and the control group were
placed in a room containing toys, including the Bobo doll, where they could play freely for 20
minutes. The results of this study showed that children in the first experimental group who
observed physical aggression by an adult were more likely to engage in that behavior
themselves. In addition, there were gender differences with boys displaying more aggression
than girls. These experiments showed that behavior could be learned through observation alone.
There are a number of ways in which social cognitive theory may be applied to the
context of this study. In particular Bandura’s research on the factors of self-efficacy and selfregulation has important repercussions for learning, especially in informal environments.
According to a meta-analyis of the impact of self-efficacy on language learning, “self-efficacy is
one of the most influential independent variables on learners’ performance and achievement
within second language learning contexts” (Raoofi, Tan, & Chan, 2012, p. 66). Based on these
finding, Raoofi et al. suggested that teachers take an active role in increasing students’ self37
efficacy by providing positive feedback and ensuring that learning tasks are appropriate for the
students’ proficency. For self-directed ML, this advice can also be applied to the design of
applications. Furthermore, computer self-efficacy is a construct utilized within some versions of
the technology acceptance model. In a recent study of 314 students enrolled in a post-graduate
certificate course, computer self-efficacy was identified as both an indirect and direct
determinent of behavioral intention to use technology (Teo & Zhou, 2014).
The ability to self-regulate behavior has also been shown to be an important predictor of
language learning success; however, factors such as low self-efficacy, excessive self-censure,
and social inhibitors can act as barriers (Shirkhani & Ghaemi, 2011). Like self-efficacy, selfregulation can be influenced by intervention either by an instructor or the system being used.
Rowe and Rafferty (2013) provide numerous examples of the use of such prompts in e-learning
and demonstrated that these prompts had a positive effect on increasing students’ ability to selfregulate their learning. While there are certainly differences between formal e-learning
environments and informal ML environments, they are similar in the need for increased selfregulation on the part of the student due to the distance from or absence of an instructor.
Therefore, designers of informal ML applications may be able to increase self-regulation through
the use of prompts built into the system.
Social cognitive explanations of observational learning are also pertinent to the context of
this study. For language learners, the use of technology, especially ubiquitous technology like
mobile devices, facilitates access to authentic materials and target language speakers, which may
increase the opportunity to take part in observational learning. One of the most important, yet
controversial theories of SLA is the input hypothesis, which sees output as merely a by product
38
of comprehensible input (Krashen, 1981, 1985, 1992). This model seems to be congruent with
Bandura’s concept of vicarious learning that asserts that individuals can learn through the
observation of the actions of other without taking part in the action themselves. While Krashen’s
claim that input alone is sufficent to produce successful language acquistion has been disputed
by many researchers in the field, few would argue that input is not a necessary component of
SLA. Therefore, because mobile devices can provide near constant access to this input, as well
as the instructional scaffolds necessary to improving comprehension, they are becoming vital
tools in foreign language learning (Vavoula et al., 2005).
Informal Learning
Learning can occur in three settings: formal, non-formal, and informal (Stevens, 2010).
Formal learning is what is experienced from preschool to graduate school. According to
Merriam et al. (2007), this type of learning usually takes place in a classroom setting and
involves qualified teachers, structured curriculums, and formal recognition of achievements. In
contrast, non-formal learning takes place outside of our primary schooling and is often voluntary.
After-school educational programs and athletic clubs fall into this category. While not as
structured as formal study, non-formal study usually involves a teacher or facilitator and a
curriculum. In contrast to formal and non-formal learning, informal learning occurs outside of a
classroom or institution, and is driven by the interests of the learner rather than an externally
imposed curriculum (Laurillard, 2009). Because university students decide for themselves what
and how they study, informal learning is often categorized as self-directed. Tough (1979), for
example, posited that informal learning is a conscious effort of the learner to seek information
about a subject of interest to her or him, and is a means to gain new information to satisfy an
39
immediate need or accomplish a goal. However, not all definitions limit informal learning by the
self-directedness of the learner or the presence of an immediate need. For example, Livingstone
(2001) makes no distinction between conscious or unconscious informal learning and only states
that informal learning takes place outside of the formal curricula of an educational institution.
According to Vavoula et al. (2005), informal learning includes activities where the learner is
intentionally engaging in a learning project in order to achieve a specified outcome as well as
unintentional learning, which occur without the conscious knowledge of the participant. Stevens
(2010) put forth this definition of informal learning, which encompasses both self-directed and
incidental learning:
Learning resulting from daily life activities related to work, family or leisure. It is not
structured (in terms of learning objectives, learning time or learning support) and
typically does not lead to certification. Informal learning may be intentional but in most
cases it is non-intentional (or ‘incidental’/ random). (p. 12)
Several studies have shown that informal learning is widespread among adults.
According to an estimate of Tough’s 1970s studies on informal learning, 98% of learners
engaged in some form of a self-directed learning project for an average of 500 hours a year
(Livingstone, 2001). In a series of studies conducted by Livingstone, Hart, and Davie in 1996,
1999, and 2000, over 80% of participants reported learning informally, and did so for 600 hours
or more a year (Livingstone, 2001). In contrast to these findings, a study of adult learning in
Finland showed that only one-fifth of the population engaged in informal learning activities each
year (Blomqvist, Ruuskanen, Niemi, & Nyssonen, 2000). However, the disparity in informal
learning participation between these two countries may be explained by the fact that the
40
researchers in the Finnish study only considered data from respondents who performed selfdirected learning for 20 hours a week or more. More recent studies in informal learning have
highlighted the effect that ICT has on informal learning. According to a 2009 survey conducted
in the United Kingdom, 94% of respondents participated in informal learning in the previous
three months and 74% of those surveyed used some form of technology to facilitate this learning
(Hague & Logan, 2009). While this research investigation did not focus on language learning, it
is nevertheless an area of study where knowledge is often acquired in an informal environment.
In fact, everyone acquires his or her first language informally with little explicit instruction.
Second and foreign languages are also studied in informal environments either out of necessity
when immigrating, visiting, or working in another country, or for enjoyment as a hobby. Like
other forms of informal learning, language study can be facilitated by the use of technology,
which provides students with unlimited access to content in the target language.
Informal language learning. Research conducted in France observed EFL students
usage of ICT for informal learning (Sockett & Toffoli, 2012; Toffoli & Sockett, 2010). In the
first study, the researchers found that 60% of participants used the Internet to download English
media and 30% of participants used social networking sites (SNSs) such as Twitter and
Facebook to communicate in English (Toffoli & Sockett, 2010). In a follow-up study, Toffoli
and Sockett (2012) sought to examine if participants in their earlier research continued to interact
with the target language speakers and materials they came into contact with, whether the students
functioned in an authentic virtual community, and how these interactions affected language
proficiency. The findings were positive confirming that participants continued their interaction
in these virtual communities, became authentic members, and as a result improved their English
41
skills. Research by Nielson (2011) examined the usage of off-the-shelf self-study language
learning software in the workplace. The software utilized in the study was Auralog’s TELL ME
MORE and Rosetta Stone. Unfortunately, the attrition rate was very high, which made it
difficult to assess whether usage of these programs would result in gains in language learning
proficiency. Based on these findings, Nielson concluded that off-the-shelf self-study software
packages were not a viable solution for workers and should only be considered as a supplement
to teacher-led instruction. In contrast to these negative results, research regarding games and
simulations for language learning showed these mediums were beneficial for improving
proficiency and motivating student participation (Peterson, 2009; Young et al., 2012). These
results demonstrate the importance of design in computer-based language learning materials,
especially when they are used for self-study. Furthermore, the authenticity of online
environments offers several advantages for informal learning as shown by Toffoli and Sockett
(2010) and Sockett and Toffoli (2012). While the introduction of ICTs has had a profound
impact on the way we learn languages, fixed-technologies can limit when and where we access
resources in the target language. However, advances in mobile technologies have provided
learners with a viable alternative that can facilitate the opportunity to informally learn a
language.
Mobile-Assisted Language Learning
In recent years, mobile technologies have become increasingly commonplace in the lives
of people all over the world. According to the International Telecommunication Union (2014),
over 7 billion people, 95.5% of the world’s population, subscribe to a mobile network. In the
United States, 90% of adults own a mobile phone, and 42% own a tablet computer (Pew
42
Research, 2014). The ubiquity of mobile devices, along with their affordability, flexibility,
portability and usability (Viberg & Grönlund, 2012), has increased the mobility of society and
has had an impact on business, entertainment, and education (Traxler, 2009). In the field of
education, mobile learning (ML) has become an area of growing interest among teachers and
researchers. This is evidenced by an increased reference to ML in education-based literature and
the development of specialized publications, conferences, and workshops dedicated to the
subject (Traxler, 2009). As a result, a number of studies have been conducted in higher
education to investigate the effectiveness of ML across diverse disciplines. One of the most
studied applications of ML is MALL - the use of mobile devices in second language acquisition
(Kukulska-Hulme, 2013). MALL researchers have described the use of mobile devices to
facilitate language learning in a number of ways including Quick Response (QR) codes (Liu,
Tan, & Chu, 2010), GPS (Ogata et al., 2008), mobile applications (Godwin-Jones, 2011) and
Twitter (Borau, Ullrich, Feng, & Shen, 2009). While the vast majority of MALL research takes
place in formal education environments, these studies often make use of students’ personal
mobile devices and deliver flexible and contextualized learning outside of the classroom. For
this reason, studies in formal MALL can provide insights into the usage of mobile devices for
informal language learning. This is important due to a lack of studies of MALL in informal
contexts. With this in mind, the following review of informal MALL research will begin with a
general examination of the definitions, devices, affordances, and challenges of ML and MALL
and conclude with a description of empirical studies of informal MALL.
Definitions. As an emerging field, consensus on the definition of ML has remained
elusive (Kukulska-Hulme, 2009). According to Traxler (2009), a clear definition is important in
43
affecting perceptions of the field and determining its future growth. Many definitions of ML
tend to concentrate on the device, and as a result are limited by a techno-centric view, which
emphasizes the mobility of technology while ignoring the mobility of the learner (KukulskaHulme, 2009; Viberg & Grönlund, 2012; Wong & Looi, 2011). While several researchers
criticize this focus on technology over other defining factors they also acknowledge the
important role that devices currently play in ML (Kukulska-Hulme, 2009; Traxler, 2009). For
example, a dedicated MP3 player such as an iPod Nano can facilitate listening based activities,
but cannot be used for delivering videos to students. For this reason, research on MALL usage is
often categorized by device (e.g. Kukulska-Hulme & Shield, 2008; Stockwell, 2012b).
Devices. The definition of a mobile device is not completely agreed upon by researchers
in the field. While some researchers limit the definition to handheld devices that can be used on
the move (Yang, 2013), others include devices such as laptop computers in their definitions
(Stockwell & Hubbard, 2013). The vast majority of MALL research has focused on three
devices – MP3 players, personal digital assistants (PDAs), and mobile phones (Stockwell &
Hubbard, 2013; Stockwell, 2012b); however, as new and better technology is introduced the
focus of ML research has also changed. While research on the use of PDAs was prominent at
one time, there has been a shift to research concentrating on mobile phones in recent years
(Stockwell, 2012b). The reason for this change in focus can be attributed to the development of
mobile phone technology and widespread ownership of these devices (Stockwell, 2012b). While
access to mobile phones is high and most models are capable of a variety of functions, the small
screen size and slower speed of input on these devices can present challenges to their effective
use in education (Stockwell, 2008; Thornton & Houser, 2005; Wang & Higgins, 2006).
44
Tablet computers may reduce or eliminate some of these limitations, but like PDAs,
access is a limiting factor (Chen, 2013). Other mobile devices that have been used to facilitate
MALL are e-book readers (Chiang, 2012), multi-media players (Ducate & Lomicka, 2013),
electronic dictionaries (Dashtestani, 2013), and portable game consoles (Kondo et al., 2012).
Although laptops are still the most prevalent technology used by undergraduate students for
educational purposes (Dahlstrom, Walker, Dziuban, & Morgan, 2013), there is some controversy
as to whether or not they are mobile devices (Viberg & Grönlund, 2012). Traxler (2009) argued
that while laptop computers are more portable than fixed technologies, they are not
“normalized.” Normalization is when a technology is integrated into the lives of users so
thoroughly that it becomes virtually invisible (Bax, 2003). A mobile phone fits this description,
but laptops are usually only carried by an individual when they have a specific use planned for
the device at some point in the day (Stockwell, 2012b). The recent development of ultra-light
laptops such as the MacBook Air and laptop/tablet hybrids like the Surface Pro might challenge
these assumptions. However, these technologies still require the user to stop and use the device
when on the move, which limits mobility even if the technology is well integrated into the user’s
lifestyle. Finally, wearable devices are an emerging mobile technology that could provide
language learners with increased device integration and access to learning materials at the point
of need. Google Glass when coupled with an application such as Word Lens, which provide real
time translation of text, is an example of such a technology that could be applied to MALL.
Affordances. Mobile devices provide a number of benefits for learners, teachers, and
universities wishing to utilize technology for educational purposes. One of the most cited
benefits of ML is the increased flexibility it provides learners (Liu, Han, & Li, 2010; Valk,
45
Rashid, & Elder, 2010; Viberg & Grönlund, 2012). Flexibility is characterized by access to
learning materials at any time or place (Valk et al., 2010) and the advantage of being able to
utilize them for short periods of time, while commuting or waiting in line, to engage in learning
(Stockwell, 2012b). In addition, ML is associated with lower costs to both students and
organizations (Abu-Al-Aish & Love, 2013; Viberg & Grönlund, 2012). One reason for this is
because mobile technologies are usually less expensive than fixed-technologies to purchase and
maintain (Abu-Al-Aish & Love, 2013). Furthermore, because ML often makes use of students’
personal devices, participants are more familiar with the technology, which reduces training time
and costs (Mehdipour & Zerehkafi, 2013). Mobile devices also facilitate situated and authentic
learning (Traxler, 2009), which encourages students to take greater responsibility for their
education (Comas-Quinn et al., 2009). This increased sense of responsibility can then increase
motivation. Stockwell (2012b) described the use of global positioning systems (GPSs) to
provide learners with situated and authentic language learning materials through the following
example:
We might imagine a situation where a person is studying Japanese in Australia, for
example. Their mobile phone has an application installed that accesses their location
using the built-in GPS feature. As they walk down the street, the application senses that
these is a Japanese restaurant nearby, and sends a message to the person along with a list
of vocabulary that might be useful with regard to Japanese food. (p. 212)
Finally, studies in MALL have demonstrated several specific advantages to secondlanguage acquisition in learners (Viberg & Grönlund, 2012). These benefits include increased
time spent on language learning tasks (Stockwell, 2010), increased motivation and engagement
46
(Comas-Quinn et al., 2009) as well as improvements in listening, speaking, and vocabulary
development (Viberg & Grönlund, 2012).
Challenges. Despite the numerous advantages that mobile devices afford both learners
and teachers, there are several barriers that must be addressed in order to make effective use of
this technology. The limitations of mobile devices for learning can be categorized as physical,
psychological, and pedagogical (Stockwell, 2012b). While some limiting characteristics span all
devices, many of the issues are device-specific. This is especially true of physical limitations.
Physical limitations refer to technical and dimensional characteristics of a mobile device
that constrains usability. On small devices such as mobile phones, screen size and resolution can
pose a problem for learners (Maniar, Bennett, Hand, & Allan, 2008; Stockwell, 2010).
Furthermore, due to the reduced size of keyboards on these devices, the speed of data input can
be limited (Maniar et al., 2008; Stockwell, 2012b), which increases the time required to complete
activities and the number of mistakes students make (Stockwell, 2010). Additional physical
limitations of mobile devices cited in the literature are limited memory (Elias, 2011; Koole,
2009) and slower processing speeds (Koole, 2009) when compared to fixed technologies. While
tablet computers may relieve some of these issues, reduced access to these devices and the
resulting unfamiliarity with their operation can increase both cost and training time (Brown,
Castellano, Hughes, & Worth, 2012).
Psychological barriers towards the use of mobile devices for learning can also reduce
adoption. The EDUCAUSE Center for Analysis and Research (ECAR) Study of Undergraduate
Students and Technology 2013, which surveyed 113,035 students in 13 countries, showed that
university students were eager to use mobile technologies for learning but were concerned with
47
issues related to privacy and boundaries between private and study time. In addition, many
students see certain mobile devices, especially their personal mobile phones, as tools for
entertainment and personal communication rather than study (Kondo et al., 2012; S. Wang &
Higgins, 2006). Finally, while one of the major advantages of ML is that students can access
instructional materials at any time and place, there is a preference among learners to study for
longer periods of time in fixed locations, which can negate the advantages afforded by mobile
technology (Stockwell, 2012b).
Lastly, pedagogical limitations can also prevent successful implementation of ML. First,
mobile devices can serve as both a distraction to students (Crescente & Lee, 2011) as well as a
potential disruption to classroom activities (Masters & Ng’ambi, 2007). It is for these reasons
that many educators hesitate to use mobile devices in their classes, and several institutions have
instituted policies banning these technologies. Second, students will undoubtedly own a variety
of mobile devices. In one study which investigated students’ informal use of their personal
mobile devices for learning, researchers discovered that students were using 13 different mobile
phone models (Santos & Ali, 2011). This can make it difficult for teachers to manage activities
and troubleshoot when students experience technical problems. Third, there is a tendency for
educators and researchers to use computer-assisted language learning methodologies when
delivering instruction through mobile devices without modifying language-learning activities to
address either the advantages or limitations of the technology (Stockwell, 2012b).
Informal mobile-assisted language learning. Many researchers identify mobile devices
as ideal tools to facilitate informal learning due to access, portability, and the flexibility with
which they can be used. Several studies in ML have investigated the ways in which university
48
students utilize their personal mobile devices to facilitate informal learning. A 2011 study
conducted by Santos and Ali in the United Arab Emirates showed that 53% of students engaged
in informal learning activities frequently using mobile devices and usually did so in their homes.
The most used application for informal learning was text messaging, which students used to
contact classmates regarding course content. While the results of this study provide important
information regarding student usage of mobile devices for learning outside of class, it is
important to note that Santos and Ali (2011) only questioned students about activities related to
course content. According to many definitions of informal learning, learning activities
connected with formal classroom environments should not be considered informal. However,
Santos and Ali (2011) prescribed to a broader definition, which encompassed any educational
activity that took place outside of the classroom.
In Japan, Barrs (2011) researched how students were using smartphones for language
learning both informally and as a supplement to classroom activities. Despite the small number
of participants in his study, Barr (2011) showed that students were using their smartphones in a
variety of innovative ways. This included using the phone’s built-in camera to take pictures of
the whiteboard, and the use of a flashcard application. In addition, students reported using their
smartphones to access a variety of authentic language materials such as news and music videos.
Finally, there are several research studies that have attempted use mobile devices to
bridge formal and informal activities. Geotagging is one way in which researchers are using
students’ mobile devices to provide language practice outside of the classroom in the hopes of
encouraging informal learning. In Denmark, high school and university students studying
Danish as a second language used their mobile phones to access geotags, which link specific
49
locations with media such as photographs, video, and audio, to extend language learning outside
of the classroom (Bo-Kristensen, Ankerstjerne, Wuff, & Schelde, 2009). The students began by
completing a pre-activity such as watching a video of a conversation in Danish and comparing
those conversations with ones they have in their native language. Next, students accessed
additional videos of conversations geotagged to locations in the town where they were studying.
These conversations were context-specific; for example, a discussion regarding fashion would be
geotagged to a clothing store. When students used Danish in their daily lives, they were asked to
create an artifact of the event by taking a picture or making an audio recording of a discussion
via their mobile phones and then report back to their classmates.
Mobile GPS technology has also been used in several studies conducted in Japan for the
learning of Japanese and English-language vocabulary. The Japanese Polite Expressions
Learning Assisting System (JAPELAS) helped students of Japanese as a second language
address interlocutors with the correct level of politeness - an important consideration in a
language that contains three distinct registers - based on several factors including the student’s
location and personal information (Yin, Ogata, Tabata, & Yano, 2010). Another mobile system
called TANGO – the Japanese term for “word” – used radio frequency identification tags in
objects to assist students in learning vocabulary (Ogata, Yin, El-Bishouty, & Yano, 2004).
Finally, Ogata et al. (2008) developed the LOCH (Language Learning Outside of the Classroom
with Handhelds) system; a GPS enabled mobile application that facilitated communication using
the target language in social situations while providing learners with support and feedback.
An additional application of mobile devices is their use to scaffold students’ informal
language learning while watching television. In two studies (Fallahkhair, Pemberton, &
50
Griffiths, 2005; 2007), researchers described the process of creating and field-testing the
Television and Mobile Phone Assisted Learning Environment (TAMALLE) system, which
provided learners with supplementary information regarding television programs to scaffold use
of this media for informal language learning.
Comas-Quinn, Mardomingo, and Valentine (2009) utilized mobile blogging for students
to share their study abroad experiences. In this paper the researchers described a pilot study
involving eight students studying Spanish as a second language in Santiago, Chile. Using their
personal mobile phones, students were asked to create multimedia blog entries using text, audio,
images, and video and upload their posts to a class website. Over one week students uploaded
two images, three audio recordings and responded to 25 posts. The researchers concluded that
the use of mobile blogs for informal language learning was a viable activity, but in order to
ensure adequate participation, instructors needed to support and encourage students.
Finally, Chen (2013) distributed tablet computers to students in China to examine how
they were used for informal English study. This research study consisted of two cycles, which
were each one-week in length. During the first cycle, students received their tablets and
participated in a short orientation session regarding their use. After the orientation session,
participants were allowed carry the tablets wherever they went, but were told to use them mostly
for English study. In order to observe how the devices were being used and identify challenges
to their implementation, the learners completed a daily usage diary and participated in a 30minute group interview at the end of the week. Based on the data collected in cycle one, the
researcher made a revised plan for cycle two of the study. This consisted of dealing with
technical problems that occurred in the first week, and creating communicative and collaborative
51
mobile platforms using social media. The researcher found that while students had positive
attitudes towards the use of tablet computers for informal English language learning, the
participants, like those in Comas-Quinn et al.’s (2009) research, needed support from their
instructors to make full use of the technology.
Technology Acceptance
The Technology Acceptance Model (TAM), developed by Davis (1989), is one of the
most used and validated measures of technology acceptance in the academic literature (King &
He, 2006; Legris, Ingham, & Collerette, 2003; Teo, 2010). Davis, Bagozzi, and Warshaw (1989)
have stated that the purpose of the TAM is “to provide an explanation of the determinants of
computer acceptance that is generally capable of explaining user behavior across a broad range
of end-user computing technologies and user populations, while at the same time being both
parsimonious and theoretically justified” (p. 985). The original TAM identified three constructs
including perceived use, perceived ease of use, attitudes towards use, behavioral intention, and
actual use. The constructs of the traditional TAM can predict 40% of system use. Over the years
a number of different versions of the TAM have been developed in an effort to improve the
model. These permutations include the TAM2 (Venkatesh & Davis, 2000), the Unified Theory
of Acceptance and Use of Technology (Venkatesh, Morris, Davis, & Davis, 2003), and the
TAM3 (Venkatesh & Bala, 2008). In addition, variations of the TAM have been created to
support technology acceptance research for a variety of technologies and learning environments.
Technology acceptance and informal learning. Given the advantages that technology
provides for informal learning, one would think that a rich body of literature would have been
developed on the acceptance of technology in this environment. In fact, Straub (2009) in an
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article describing various models of technology adoption and acceptance stated that future
research in that field should concentrate on informal settings. However, the majority of research
on the use of technology for informal learning has focused on usage.
Chen’s (2013) research study is one of the few attempts to investigate user acceptance of
technology in an informal environment. In this study, Chen (2013) distributed tablet computers
to university students studying EFL. The participants were instructed to keep a record of their
usage of these tablets for language study, and to complete a survey based on the TAM using the
constructs of usability, effectiveness, and satisfaction. The results showed that students found
tablet computers to be easy to use, effective and that they were satisfied with this technology for
informal language study.
While few research studies on technology acceptance in informal learning environments
exist there are several studies that have examined the factors that affect acceptance of
technologies for personal use among university students. For example, studies have been
conducted in Saudi Arabia (Nassuora, 2013) and Tunisia (Nasri & Charfeddine, 2012) to assess
acceptance of the social networking site (SNS) Facebook. While these studies did not examine
the usage of SNS for learning, they did provide information regarding the determinants of usage
of a technology that students were using voluntarily as they would in an informal learning
situation.
In addition to personal use technologies, we might also gain a better understanding of
technology acceptance in informal learning by examining studies of m-learning acceptance. This
is because m-learning often occurs outside of the classroom where students are engaged in selfdirected or self-regulated learning. In addition, in some cases participants are even using their
53
personal devices. Although learners in formal m-learning environments may lack the agency to
choose the task with which they engage, many of the affordances and challenges associated with
the use of mobile devices outside of the classroom setting will be similar.
Research model. The research model that will be employed in this study is a
modification of the unified theory of acceptance and use of technology (UTAUT) created by
Abu-Al-Aish and Love (2013). The UTAUT was an effort to review and synthesize eight
models that have been used to study technology acceptance including theory of reasoned action,
technology acceptance model (TAM), motivation model, theory of planned behavior, combined
TAM and TPB, model of personal computer utilization, innovation diffusion theory, and social
cognitive theory. Drawing from these models, Davis et al. (2003) created a research paradigm,
which accounted for four direct determinants of intention or actual usage and four indirect
determinants. The four direct determinants were performance expectancy, effort expectancy,
social influence, and facilitating conditions. The four indirect determinants were gender, age,
experience, and voluntariness of use. The results of Venkatesh et al. (2003) research provided
strong evidence for the use of UTAUT to predict technology usage. In fact, the constructs used
in UTAUT were found to predict 70% of variation in usage as opposed to 40% when using the
traditional TAM.
Wang, Wu, and Wang (2009) utilized a modified version of UTAUT by adding the
constructs of perceived playfulness and self-management of learning to examine ML acceptance.
The results of their study demonstrated that performance expectancy, effort expectancy, social
influence, perceived playfulness, and self-management were significant predictors of behavioral
intention to engage in m-learning. A 2010 study by Lowenthal of 113 university students
54
demonstrated that while the constructs of performance expectancy and effort expectancy were
significant predictors of intention to use mobile technology for the purpose of learning, selfmanagement was not. Finally, Iqbal and Qureshi (2012) study of m-learning acceptance among
250 university students in Pakistan showed that all of the factors they examined – ease of use,
perceived usefulness, facilitating conditions, social influence, and perceived playfulness – were
significant determiners of behavioral intention to engage in m-learning.
Based on the findings of these previous studies, Abu-Al-Aish and Love (2013) developed
a modified UTAUT with the intention of improved prediction of behavioral intention to use mlearning. Their research model identified five constructs as key determiners: (1) performance
expectancy, (2) effort expectancy, (3) social influence (lecturers), (4) quality of service, and (5)
personal innovativeness. One mediating factor was hypothesized – mobile device experience.
55
Figure 1. Research model of m-learning acceptance adapted from Abu-Al-Aish and Love (2013)
The results of Abu-Al-Aish and Love’s (2013) research showed that the five main
constructs of performance expectancy, effort expectancy, social influence, quality of service, and
personal innovativeness were all significant in determining behavioral intention to use mlearning. In addition, mobile device experience had a significant moderating effect on all five of
the main constructs.
Performance expectancy. Performance expectancy is the extent to which an individual
believes that usage of a technology will facilitate the achievement of a given outcome
56
(Venkatesh et al., 2003). In the UTAUT performance expectancy replaced the previous
constructs of perceived usefulness, extrinsic motivation, job-fit, relative advantage, and outcome
expectations and is the most significant determinant of behavioral intention (Venkatesh et al.,
2003). In regards to ML, Wang, Wu, and Wang (2009) revealed performance expectancy to be
highly predictive of intention in this context. Abu-Al-Aish and Love (2013) suggested that the
flexibility and speed of learning afforded by mobile technologies affected students perceptions of
this construct and demonstrated that it had a direct affect on behavioral intention in ML.
Effort expectancy. Effort expectancy is the extent to which a technology is perceived as
easy to use (Venkatesh et al., 2003). This construct replaced the constructs of ease of use and
complexity which were used in earlier acceptance models (Venkatesh et al., 2003). Research
suggests that the influence of effort expectancy can differ depending on factors such as age,
gender, experience and voluntariness of use may effect perceptions of this construct (Abu-AlAish & Love, 2013; Straub, 2009). Research of ML acceptance with university students has
shown that these subjects often find mobile devices easy to use (Dashtestani, 2013; Ducate &
Lomicka, 2013). One reason for this may be the familiarity these individuals have with these
devices because of personal use.
Social influence (lecturer). Social influence is the extent to which an individual feels
that others want him or her to use a particular technology (Venkatesh et al., 2003). Social
influence replaced the constructs of subjective norm, societal factors, and image, which were
used in previous models of acceptance and adoption (Venkatesh et al., 2003). Research in social
influence has examined the effect of both superiors and peers on technology acceptance (Igbaria,
Schiffman, & Wieckowski, 1994). Due to the influence that educators exert on students to adopt
57
new technologies, Abu-Al-Aish and Love (2013) included lecturer influence as a construct in
their model of ML acceptance.
Quality of service. Abu-Al-Aish and Love (2013) based their definition of quality of
service on research in human computer interaction (Kuan, Bock, & Vathanophas, 2003) and
usability research (DeLone & McLean, 1992; Rai, Lang, & Welker, 2002). In these fields,
quality of service is related to customer satisfaction and perceptions of reliability, response,
content, and security (Abu-Al-Aish & Love, 2013). One aspect of service quality is the degree
of support provided by organizations or within the infrastructure of technology to facilitate its
use. This concept is contained within the construct of facilitating conditions in the original
UTAUT (Venkatesh et al., 2003). Research by Lim and Khine (2006) has shown that the
presence of poor facilitating conditions can act as a barrier to technology integration. In informal
ML situations, perceptions of quality of service may be complicated by the fact that service may
be provided from several sources such as the mobile device service provider or the designer of an
application used for learning. However, quality of service has been shown to be a significant
predictor of students’ acceptance of ML (Abu-Al-Aish & Love, 2013).
Personal innovativeness. Innovativeness is the degree to which an individual is willing
to try and adopt new technologies (Rogers, 2003). While not included as a construct in the
UTAUT (Venkatesh et al., 2003), the use of personal innovativeness in technology adoption and
acceptance is supported by a large body of theoretical and empirical research (Agarwal &
Prasad, 1998). Research conducted by Fagan, Kilmon, and Pandey (2012) showed that personal
innovativeness was a key determiner of student acceptance of virtual reality simulations for
learning. Abu-Al-Aish and Love (2013) demonstrated that personal innovativeness was
58
predictive of ML acceptance and hypothesized that this might be due to the propensity for highly
innovative students to take the risk of adopting a new technology.
Mobile device experience. Mobile device experience is identified in Abu-Al-Aish and
Love’s (2013) model as a moderator to the main constructs of the study. In the UTAUT,
experience was shown to have an indirect influence on the constructs of effort expectancy, social
influence, and facilitating conditions. Because mobile phone penetration rates are near 100%
among Japanese university students (Stockwell, 2008), experience with the use of mobile devices
is expected to be high.
Summary
The purpose of this review of literature was to provide readers with an understanding of
informal mobile-assisted language learning and the factors that affect acceptance of this
technology in the Japanese context. The review began with a description of higher education and
English language education in Japan. In addition, theories of adult learning and second language
acquisition were described in light of this context. Next, the literature on informal learning was
explained with particular attention given to informal language learning and the enabling effects
of technology. The unique situation regarding technology usage in Japanese higher education
was also introduced before explaining the definitions, devices, affordances, challenges and
empirical literature associated with informal mobile-assisted language learning. Furthermore,
the TAM was described as well as the application of the TAM to informal learning and ML.
Finally, the constructs that will be used for this study were defined.
59
Chapter 3: Methodology
Introduction
The purpose of this study was to examine the acceptance and usage of mobile technology
by Japanese university students for informal English-language learning. This chapter outlines
the research design, data collection, and method of data analysis that were used to investigate
this subject. In addition, a description of the research setting and participants as well as
information regarding the study’s instruments is presented. Finally, ethical considerations and
limitations of the study are discussed.
Research Questions
The following five research questions were addressed in this study:
1.
What is Japanese university students’ overall acceptance of the use of mobile devices
for informal English-language learning as measured by a quantitative scale based on
the Technology Acceptance Model (TAM)?
2.
What is their actual use of mobile devices for informal English-language learning?
3.
What is the relationship between students’ acceptance of mobile devices for informal
English-language learning and their actual use?
4.
Are there any variations in responses based on individual differences?
5.
What do students perceive as potential advantages and disadvantages of mobile
devices for informal English-language learning?
Research Design
The choice of research design is driven by one’s goals and research questions (Butin,
2010) as well as the resources to which one has access (Gall, Gall, & Borg, 2003). Because few
60
previous research studies exist on informal mobile-assisted language learning (MALL) use
among Japanese university students, one of the goals of this study was to fill this notable void in
the academic literature by collecting broad data from a large number of individuals. For this
reason, a paper-based survey instrument was used to collect data and the data were analyzed
quantitatively using descriptive and inferential statistics. In addition, open-ended questions
regarding students’ perceptions of the advantages and disadvantages of the use of mobile
technology for informal English study were analyzed using open-coding. Surveys are an
efficient and versatile tool, which allow researchers to collect large amounts of information and
to generalize the results from a relatively small sample to a larger population (Check & Schutt,
2012). Because the data were collected during one time period, the research design is considered
cross-sectional (Johnson & Christensen, 2012). Finally, the setting and research participants
were chosen due to the access provided by researcher’s position as a lecturer. This position can
provide the researcher with increased knowledge of the participants and the university (Bonner
& Tolhurst, 2002); however, as will be discussed in the limitations section of this paper, these
advantages are tempered by the potential of violating research ethics due to issues of power and
influence (Creswell, 2014). The following sections will provide additional information
regarding the setting, participants and sampling techniques employed
Research Setting
The research study took place in the Economics and Information Science Departments of
a Japanese university. This university is one of the top five private higher education institutions
in western Japan—the region of the country where the major cities of Osaka, Kobe, and Kyoto
are located. In 2014, 32,499 students were enrolled at the university’s three campuses
61
The Economics undergraduate program is divided into two tracks: general and
international. In 2014, there were 2,819 students enrolled in the general track and 739 in the
international track. Students in both tracks must successfully complete courses in
communication and writing (CW), taught by native speakers of English, and listening and
reading courses, taught by Japanese native speaking teachers. In addition, students must achieve
a satisfactory score on the Test of English for International Communication (TOEIC) in order to
graduate from the program. The Economics and International Economics programs differ in
several ways. International Economics students enjoy smaller CW classes, no more than 15
students per class, and have the option to study an additional foreign language in their second
year. Students in these programs tend to possess a higher proficiency in English than students in
the general track program. In addition, International Economics program students are more
likely to participate in a study abroad program during their undergraduate studies. For these
reasons, there might be important differences between students in these programs in regards to
their participation in and acceptance of informal English-language study.
The Information Science Department is smaller than the Economics Department with a
total enrollment of 2,009 students in 2014. First- and second- year Information Science students
must complete a series of ten English courses to fulfill their degree requirements. Courses are
categorized by language skill—speaking and listening, reading and writing, and computerassisted language learning (CALL). The following table shows the 10 courses divided by skill
and semester:
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Table 1
Information Science English Classes by Skill and Semester
Fall Semester
Spring Semester
Speaking and Listening
E1 and E7
E4 and E9
Reading and Writing
E2 and E8
E5 and E10
CALL
E3
E6
Note: E1 – E5 course are taken by first-year students while E6 – E10 are taken by second-year
students
Participants
The population of all first- and second-year Economics and Information Science students
participating in mandatory English courses was used for this study. The survey instrument was
administered to Economics students in their CW courses and to Information Science students in
their speaking and listening courses (E1, E4, E7, and E9). The researcher administered the
survey to students in his classes and had other course instructors distribute the questionnaire in
their courses. In 2014, there were a total of 1,609 Economics students and 978 Information
Science students in their first and second year of study. Each semester, these students are
enrolled in approximately 48 CW courses in the Economics Department and 16 speaking and
listening courses in the Information Science Department. An effort was made to distribute the
survey to all of these courses because a greater number of participants will lead to a more robust
study and increase the potential of finding significant results (Suresh & Chandrashekara, 2012).
While students from all over the world attend Japanese universities, over 90% of students
are ethnically Japanese and enter the university around the age of 18 (Fuwa, 2009). Because
elementary, junior, and senior high school education is uniformly regulated by the Ministry of
63
Education, Culture, Sport, Science, and Technology (MEXT), most students come from a similar
educational background, which includes at least 6 years of formal English education (MEXT,
2011a). Furthermore, Japan has a relatively small disparity of wealth among its citizens, with a
Gini index of 37.6 in 2008 (Central Intelligence Agency, 2014). Therefore, it’s relatively safe to
assume most students come from similar socio-economic backgrounds.
Instrumentation
The survey instrument for this study consisted of four sections: (1) acceptance of mobile
devices for informal English-language learning, (2) usage of mobile devices for informal
English-language learning, (3) demographics, and (4) open-ended questions (Appendix A).
Section one was an adaption of a mobile learning (ML) acceptance scale developed by
Abu-Al-Aish and Love (2013). The scale was based on the Unified Theory of Acceptance and
Use of Technology (UTAUT) (Venkatesh et al., 2003), a variation of the original Technology
Acceptance Model (TAM) (Davis, 1989), and contained 26 items divided into six constructs: (1)
performance expectancy, (2) effort expectancy, (3) lecturers’ influence, (4) quality of service, (5)
personal innovativeness, and (6) behavioral intention. A 5-point Likert scale was utilized in the
original scale with the following responses: 1 (strongly disagree), 2 (disagree), 3 (neutral), 4
(agree), and 5 (strongly agree).
After gaining permission to use and modify the scale by the authors (Appendix B), two
adaptations were made to the scale items. First, the original 5-point Likert-scale was converted
to a 4-point scale to address the tendency of Japanese students to choose a neutral response in
order to avoid confrontation (Carless, 2012; Wang, Hempton, Dugan, & Komives, 2008). In
addition, changes were made to reflect the focus of this study on the use of mobile devices for
64
informal language learning rather than ML in general. Table 2 shows the original survey items
and how they were modified for this study:
Table 2
Original and Modified Scale Items
Performance Expectancy
Original Scale Item
Modified Scale Item
PE1 I find m-learning useful for my
studies.
I find mobile devices to be useful for
informal English study.
PE2
Using m-learning would enable me
to achieve learning tasks more
quickly.
Using mobile devices would enable me
to complete informal English learning
tasks more quickly.
PE3
Using m-learning in my studying
would not increase my learning
productivity.
Using mobile devices would not
increase my informal English-language
learning productivity.
PE4
Mobile learning could improve my
collaboration with classmates.
Mobile learning could improve my
collaboration with classmates.
PE5
Using m-learning would not
improve my performance in my
studies.
Using mobile devices for informal
English-language learning would not
improve my performance.
Effort Expectancy
EE1
I would find an m-learning system
flexible and easy to use.
I find mobile devices for informal
English-language learning flexible and
easy to use.
EE2
Learning to operate an m-learning
system does not require much effort.
Learning to operate a mobile device for
informal English-language learning
does not require much effort.
EE3
My interaction with an m-learning
system would be clear and
understandable
My interaction with mobile devices for
informal English-language learning
would be clear and understandable.
EE4
It would be easy for me to become
skillful at using an m-learning
system.
It would be easy for me to become
skillful at using mobile devices for
informal English-language learning.
65
Lecturers' Influence
Original Scale Item
Modified Scale Item
LI1 I would use m-learning if it was
recommended to me by my lecturers.
I would use mobile devices for
informal English-language learning if
my instructors recommended it to me.
LL2
I would like to use m-learning if my
lecturers’ supported the use of it.
I would like to use mobile devices for
informal English-language learning if
my instructors supported the use of it.
LL3
Instructors in my department have not
Lecturers in my Department have not
been helpful in the use mobile devices
been helpful in the use of m-learning.
for informal English-language learning.
Quality of Service
Original Scale Item
Modified Scale Item
QoS1 It is important for m-learning
services to increase the quality of
learning.
QoS2
I would prefer m-learning services to I would prefer m-learning services to be
be accurate and reliable.
accurate and reliable.
QoS3
It is not important for m-learning
services to be secure to use.
QoS4
QoS5
QoS6
It is important for m-learning to
focus on the speed of browsing the
internet and obtaining information
quickly.
Communication and feedback
between lecturers and students
would not be easy using m-learning
systems.
It is preferable that m-learning
services are easy to navigate and
download.
Personal Innovativeness
Original Scale Item
It is important for m-learning services to
increase the quality of learning.
It is not important for m-learning
services to be secure to use.
It is important for m-learning to focus
on the speed of browsing the internet
and obtaining information quickly.
Communication and feedback between
lecturers and students would not be easy
using m-learning systems.
It is preferable that m-learning services
are easy to navigate and download.
Modified Scale Item
66
PInn1 It is important for m-learning
services to increase the quality of
learning.
PInn2
When I hear about a new information
I would prefer m-learning services to
technology I look forward to examining
be accurate and reliable.
it.
PInn3
It is not important for m-learning
services to be secure to use.
Behavioral Intention
Original Scale Item
I like to experiment with new
information technologies.
Among my peers, I am usually the first
to try out a new innovation in
technology.
Modified Scale Item
BI1 I plan to use m-learning in my
studies.
I plan to use mobile devices for
informal English-language learning.
BI2
I predict that I will use m-learning
frequently.
I predict that I will use mobile devices
for informal English-language learning
frequently.
BI3
I intend to increase my use of mobile
I intend to increase my use of mobile
devices for informal English-language
services in the future.
learning in the future.
BI4
I will enjoy using m-learning
systems.
I will enjoy using mobile devices for
informal English-language learning.
BI5
I would recommend others to use mlearning systems.
I would recommend others to use
mobile devices for informal Englishlanguage learning.
The second section of the survey instrument was a frequency scale measuring students’
usage of mobile devices for informal English study. The researcher developed this scale based
on two categorizations of mobile device usage (Cheung & Hew, 2009; Patten, ArnedilloSánchez, & Tangney, 2006), a prior instrument (Santos & Ali, 2011), and the researcher’s
observations and experience teaching in the Japanese university setting. Participants were asked
how often they engaged in a series of informal English-language learning activities with a mobile
67
device. Responses were recorded using a 5-point Likert scale with the responses of 1 (never), 2
(rarely), 3 (occasionally), 4 (frequently), and 5 (very frequently).
The third section of the survey instrument consisted of six demographics questions: (1)
age, (2) gender, (3) major (general or international economics), (4) class standing, (5) device
ownership, and (6) nationality. Gathering demographic data is especially important when using
a convenience sample in order to ensure that the sample adequately represents the population to
which the results will be generalized (Johnson & Christensen, 2012).
The final section of the survey consisted of two open-ended questions. The purpose of
these questions was to discover students’ perceptions of the advantages and disadvantages of the
use of mobile devices for the purpose of informal English-language learning.
The instrument was presented to the participants in a paper-based form in an effort to
increase the response rate. The researcher’s experience has shown that Japanese university
students are more likely to participate in research when a paper-based survey instrument is used
as opposed to a digital one. This may be because the Japanese educational system has embraced
digital technology at a slower rate than other developed nations (Aoki, 2010; Latchem et al.,
2008), which has made students more comfortable with paper-based materials.
Reliability and Validity
Several measures were taken by the researcher in order to ensure the reliability and
validity of the survey instruments. The researcher began by making use of a scale with
established reliability and validity. This was the case for section one of the survey instrument
(acceptance of mobile devices for the purpose of informal English-language learning).
According to Abu-Al-Aish and Love (2013), the results of an exploratory factor analysis showed
68
that, “the measurement model exhibits adequate reliability, convergent validity, and discriminant
validity” (p. 95). The Cronbach’s alpha coefficients for Abu-Al-Aish and Love’s (2013)
subscales were 0.778 for performance expectancy, 0.820 for effort expectancy, 0.812 for
lecturers’ influence, 0.718 for quality of service, 0.847 for personal innovativeness, and 0.834 for
behavioral intention. However, because the instrument was translated it may not retain previous
measures of reliability and validity (Creswell, 2014). The usage measure, while based on the
research literature, was a creation of the researcher.
A native-speaker of Japanese with a high-proficiency in English, as measured by the
TOEIC, translated the instrument (Appendix C). A second native Japanese speaker with similar
proficiency in English reviewed the translation and recommend changes. After the instrument
was translated, the researcher conducted a pilot study with an intact class of students who were
excluded from the actual study. Data collected through this pilot study were used to calculate
reliability coefficients for the scale and subscales using Conbrach’s alpha.
Data Collection
The instrument was distributed to students during their mandatory English classes, but
was completed outside of class. The survey took approximately 15 minutes to complete. Before
data collection begun, the researcher talked to all faculty members teaching CW courses in the
Economics Department and speaking and listening courses in the Information Science
Department and requested their cooperation in distributing questionnaires in their classes. For
each instructor who chose to participate, the researcher printed out all the necessary copies of the
translated survey instrument (Appendix C) and cover letter (Appendix D) and explained the
research and procedures to him or her. The cover letter was used to explain the purpose of the
69
research to students, the procedure to fill out the survey, and the students’ rights as participants.
Faculty members were provided with copies of the survey (Appendix A) and cover letter
(Appendix E) in English.
Data Analysis
Table 2 provides an overview of the data analysis process. A more in-depth description
follows the table.
Table 3
Overview of the Data Analysis Process
Research Question
Data Sources
Analysis
1. What is students’ overall
acceptance of the use of
mobile devices for
informal English language
learning?
2. What is students’ actual
use of mobile devices for
informal English language
learning?
3. What is the relationship
between students’
acceptance of mobile
devices for informal
English language learning
and their actual use?
4. Are there any variations in
responses based on
individual differences?
Acceptance of Mobile
Devices for Informal English
Learning (1)
•
Usage of Mobile Devices for
Informal English Learning
(2)
•
Acceptance of Mobile
Devices for Informal English
Learning (1) and Usage of
Mobile Devices for Informal
English Learning (2)
•
Acceptance of Mobile
Devices for Informal English
Learning (1) and Usage of
Mobile Devices for Informal
English Learning (2)
Demographic (3)
Open-Ended Questions (4)
•
5. What do students perceive
as potential advantages
70
•
•
•
Frequencies, means, and
standard deviation
Charts
Frequencies, means, and
standard deviation
Charts
Pearson’s Product
Moment Correlation
Scatter Plots
•
Analysis of Variance
(ANOVA)
Independent t Tests
•
Open-coding
and disadvantages of
mobile devices for
informal English-language
learning?
Survey data were analyzed quantitatively using IBM SPSS. Prior to conducting any
analysis the data were examined for outliers, missing values, statistical assumptions, and
negatively worded items were reverse coded. Overall scale items were created for the
acceptance scale and subscales by taking an average of the items that make up each construct.
Frequencies and percentages were calculated for demographic items.
In order to answer research questions one and two, frequencies were generated for
acceptance and usage items and descriptive statistics were calculated for overall scale items
(acceptance and usage) and the acceptance subscales. Descriptive statistics were utilized to
summarize and explain the data and included measures of central tendency and standard
deviation. Charts were also used to provide a pictorial depiction of the data (Johnson &
Christensen, 2012).
Next, scatterplots were created to gain an understanding of the relationship between
usage and acceptance. Research question three was addressed by calculating a Pearson Product
Moment Correlation coefficient, which describes “the magnitude and direction of association
between two variables measured on an interval (or ratio) scale” (Creswell, 2014, p. 164).
In order to address question four, a series of independent t tests and analysis of variance
(ANOVA) tests were performed. These tests were used to determine if any differences in
acceptance or usage exist between participants depending on their responses to the demographic
items on the survey instrument. Finally, open-coding was used to analyze responses to open71
ended questions. Open-coding data requires the manual sorting of data into categories which are
created by the researcher (Johnson & Christensen, 2012).
Ethical Considerations
Johnson and Christensen (2012) define ethics as “the principles and guidelines that help
uphold the things we value” (p. 99). In research, ethics need to be a primary concern of the
researcher and considered throughout the research process (Creswell, 2014). However, in
comparison to experimental research designs, survey-based research presents fewer ethical issues
(Check & Schutt, 2012). That being said, the questionnaire is an imposition, if only a small one,
on the participants’ time and privacy (Cohen, Manion, & Morrison, 2011); therefore, several
steps were taken to reduce the amount of that intrusion on the lives of the respondents. First,
students in the research study participated on a voluntary basis. Because the participants are
students at the university where the researcher teaches, it was important that an effort was made
to assure students that they were under no obligation to participate in the study, and their course
grade would not be affected if they did not participate. Second, participants were informed in
their native language of their rights and the purpose of the research. There was no risk of
physical harm from taking part in the survey, but there was a minor risk of mental distress or
discomfort. All participants were also made aware of their right to withdraw from the study at
any time. Both the anonymity of participants’ identities and confidentiality of their data were
maintained. A review of the ethical standards adhered to in the pilot study and main study was
conducted through the University of Wyoming Institutional Review Board. The board
determined that these studies were exempt from review (Appendix F). The university setting of
this study did not require a formal review of the research project.
72
Summary
This study is an attempt by the researcher to gauge the current state of the usage and
acceptance of mobile technology for informal language learning in the Japanese university
context. A paper-based survey instrument was used to collect data from participants and these
data were analyzed through statistical techniques and open-coding. While the researcher
acknowledged several limitations in the research design such as issues related to the distribution
of the survey instrument by course instructors and the unreliability of self-reported data, these
limitations are offset by the advantages of collecting and analyzing data from a large number of
participants in a short period of time. This is important because mobile devices are an emerging
technology and usage of and acceptance towards them is constantly in flux. The results will
provide researchers, teachers, and administrators with a thorough understanding of how mobile
devices are being employed by Japanese university students for the purpose of informal learning,
and the acceptance of these devices for this purpose.
73
Chapter 4: Article for Publication
Abstract
The researcher investigated the acceptance and usage of mobile devices for the purpose of
English-language learning among Japanese university students. The study was conducted at a
private university in Japan. A paper-based instrument, which was completed outside of class,
was distributed to undergraduate students enrolled in 59 required English as a foreign language
courses. The survey included four sections: (1) acceptance of mobile devices for informal
English-language learning, (2) usage of mobile devices for informal English-language learning,
(3) demographics, and, (4) open-ended questions. Nine hundred and seventy-seven students
participated in the study. The results of the study showed that Japanese university students were
open to the use of mobile devices for informal English-language learning and were already using
the devices for this purpose to listen to English-language music, as well as to access dictionary
and translation applications. However, activities that would enable students to engage in
communicative practice, such as the use of social networking sites, were under represented.
Furthermore, while participants were positive regarding the portability and convenience of the
devices for informal learning, they were concerned about health issues related to their usage and
worried that mobile learning may not be as effective as traditional methods of study. The results
of a Pearson Product Moment Correlation test demonstrated that each of the six subscales of
acceptance, as well as the total scale, was significantly correlated with the usage measure; the
total acceptance scale was also significantly correlated with participants’ reported usage of
mobile devices. Further analysis revealed that individual differences had an effect on
participants’ acceptance and usage responses.
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Keywords: mobile-assisted language learning, informal language learning, technologyacceptance model, higher education, Japanese students
75
Introduction
The ability to effectively communicate in English has become an essential skill for
workers in both private and public sector jobs throughout the world. According to the British
Council (Howson, 2013), there are over 1 billion people learning English as either a second or
foreign language. These individuals are learning the language in a variety of settings using
diversified methods of instruction or self-study. In recent years, the use of technology has
become central to the study of languages, providing students with greater access to educational
materials, authentic content, and tools to communicate with other language learners or native
speakers (Loewen, 2015). In particular, mobile devices have become popular vehicles to
facilitate language learning due to their availability and flexibility (Viberg & Grönlund, 2012).
While mobile devices such as smartphones and tablets can be used in formal and non-formal
learning settings, they are especially useful for informal learning because they are so integrated
into the lives of users (Chen, 2013; Jones, Scanlon, & Clough, 2013; Kukulska-Hulme, 2010).
In Japan, the setting for this research study, mobile devices are widely available and accessible
(Akiyoshi & Ono, 2008). For this reason, they have been seen by many educators and
researchers as ideal tools to facilitate informal mobile-assisted language learning (MALL) for
students of English as a foreign language (EFL). However, few studies have been conducted in
the Japanese university context to explore acceptance or usage of mobile devices for informal
English-language learning without researcher or instructor intervention. In order to make better
use of these technologies to provide learners with informal learning opportunities, it is important
to examine how students currently use mobile technologies for informal English-language
76
learning and their acceptance towards these devices for this purpose. This research study aims to
fill this critical gap in the literature.
Literature Review and Theoretical Framework
English Language Education in Japan
English is a required subject in the Japanese educational system where 98% of the
population studies the language for at least six years (Ministry of Education, Culture, Sports,
Science and Technology [MEXT], 2011). For Japanese people who participate in higher
education, an additional two to four years of English classes are often required. However, few
Japanese learners of English achieve practical competence in the language (Sakamoto, 2012).
The Test of English as a Foreign Language (TOEFL) is a standardized assessment of English
proficiency used around the world. The most recent results of the TOEFL ranked Japan 31st
among 35 Asian countries (Educational Testing Service [ETS], 2014). An alternative
assessment, the Education First English Proficiency Index (EF EPI), was more optimistic in its
rankings and classified Japanese adult English proficiency as moderate (EF EPI, 2015).
Furthermore, the EF EPI, which uses two tests to assess proficiency, found that the English
proficiency of women was superior to men, and city dwellers were more skilled than those in
rural areas. However, these scores have not improved in the past 7 years. Because English has
emerged as a lingua franca for international communication (Jenkins, 2014), limitations in
proficiency can have an impact on Japan’s ability to participate in both the globalized
marketplace and geopolitical arena.
For this reason, several policies to increase English proficiency have been implemented
by the MEXT. In primary and secondary schools, the number of years that students study the
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language has been increased (MEXT, 2008), and there has been an effort to employ more
communicative teaching methods instead of traditional teacher-centered instruction, which
focused on rote memorization of grammar and vocabulary (MEXT, 2011). Japanese companies
are also making changes to aid in the development of English ability among their employees.
For example, several leading Japanese companies announced in 2010 that English would be
adopted as the official language of management-level personnel beginning in 2012, and all other
employees would be required to increase English communication skills to meet basic standards
of proficiency (Asahi Shinbun, 2012). Furthermore, applicants with English proficiency or
experience studying abroad would be given preference in the hiring process. Even though these
reforms demonstrate a desire to increase English proficiency in Japan, several of the root causes
of the problem have been ignored.
A number of factors have been identified as possible barriers to the development of a
high level of English proficiency among Japanese speakers. These challenges include flaws in
the education system, which places greater emphasis on passing scholastic entrance exams than
developing communicative skills (Kikuchi, 2013; Ryan, 2009; Yashima & Zenuk-Nishide,
2004), and a lack of opportunities to interact in and be exposed to foreign languages. In addition,
there are social and cultural factors such as an aversion to making mistakes in order to save face
and a propensity towards modesty (Gudykunst & Kim, 2003) that may contribute to higher levels
of foreign-language anxiety (FLA) and a decreased willingness to communicate (WTC) in the
target language (Matsuoka, 2008; Yashima & Zenuk-Nishide, 2004).
Considering these issues, computer-assisted language learning (CALL) may offer several
advantages to the Japanese learner of English. For example, Internet enabled information and
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communication technologies (ICTs) can provide unlimited access to authentic content, learning
resources, and increase opportunities to communicate in the target language (Loewen, 2015).
Furthermore, because interaction can take place anonymously in many cases, learners may be
less inhibited and more likely to take risks, which may contribute to lower levels of FLA and an
increased WTC. Yet, unlike other developed countries, Japan has been slow to adopt ICTs,
especially in the field of education (Aoki, 2010; Latchem, Jung, Aoki, & Ozkul, 2008). The
exception to this is mobile technology, especially mobile phones, which are ubiquitous in Japan
and more accessible to marginalized groups such as women and those of lower socio-economic
status (Akiyoshi & Ono, 2008).
Mobile-Assisted Language Learning
In recent years, mobile technologies have become increasingly commonplace in the lives
of people all over the world. According to the International Telecommunication Union (2014),
over 7 billion people, 95.5% of the world’s population, subscribe to a mobile network. In the
United States, 90% of adults own a mobile phone, and 42% own a tablet computer (Pew
Research, 2014). The ubiquity of mobile devices, along with their affordability, flexibility,
portability, and usability (Viberg & Grönlund, 2012), has increased the mobility of society and
has had an impact on business, entertainment, and education (Traxler, 2009). In the field of
education, mobile learning (ML) has become an area of growing interest among teachers and
researchers. This is evidenced by an increased reference to ML in education-based literature and
the development of specialized publications, conferences, and workshops dedicated to the
subject (Traxler, 2009). As a result, a number of studies have been conducted in higher
education to investigate the effectiveness of ML across diverse disciplines. One of the most
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studied applications of ML is MALL - the use of mobile devices in second language acquisition
(Kukulska-Hulme, 2013). MALL researchers have described the use of mobile devices to
facilitate language learning in a number of ways including Quick Response (QR) codes (Liu,
Tan, & Chu, 2010), GPS (Ogata et al., 2008), mobile applications (Godwin-Jones, 2011) and
Twitter (Borau, Ullrich, Feng, & Shen, 2009). While the vast majority of MALL studies have
focused on formal environments, mobile device characteristics such as flexibility, portability,
and accessibility have made them ideal tools to facilitate informal language learning (Chen,
2013; Kukulska-Hulme, 2010).
In Japan, several studies have been conducted to examine informal MALL. Barrs (2011)
researched how students were using smartphones for language learning both informally and as a
supplement to classroom activities. Despite the small number of participants in his study, Barrs
(2011) showed that students were using their smartphones in a variety of innovative ways. This
included using the phone’s built-in camera to capture images of the whiteboard as well as the use
of flashcard applications. In addition, students reported using their smartphones to access a
variety of authentic language materials such as news and music videos.
Mobile GPS technology has also been used in several studies for the learning of Japanese
and English-language vocabulary. The Japanese Polite Expressions Learning Assisting System
(JAPELAS) helped students of Japanese as a second language address interlocutors with the
correct level of politeness—an important consideration in a language that contains three distinct
registers—based on several factors including the student’s location and personal information
(Yin, Ogata, Tabata, & Yano, 2010). Another mobile system called TANGO—the Japanese
term for “word”—used radio frequency identification tags in objects to assist students in learning
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vocabulary (Ogata, Yin, El-Bishouty, & Yano, 2004). Finally, Ogata et al. (2008) developed the
LOCH (Language Learning Outside of the Classroom with Handhelds) system; a GPS enabled
mobile application that facilitated communication using the target language in social situations
while providing learners with support and feedback.
Technology Acceptance Model
The Technology Acceptance Model (TAM), developed by Davis (1989), is one of the
most used and validated measures of technology acceptance in the academic literature (King &
He, 2006; Legris, Ingham, & Collerette, 2003; Teo, 2010). Davis, Begozzi, and Warshaw (1989)
have stated that the purpose of the TAM is,
to provide an explanation of the determinants of computer acceptance that is general,
capable of explaining user behavior across a broad range of end-user computing
technologies and user populations, while at the same time being both parsimonious and
theoretically justified. (p. 985)
The original TAM identified several constructs that determined actual use including
perceived usefulness, perceived ease of use, attitudes towards use, and behavioral intention. The
constructs of the traditional TAM can predict 40% of system use. Over the years, a number of
different versions of the TAM have been developed in an effort to improve the model. These
permutations include the TAM2 (Venkatesh & Davis, 2000), the Unified Theory of Acceptance
and Use of Technology (UTAUT) (Venkatesh, Morris, Davis, & Davis, 2003), and the TAM3
(Venkatesh & Bala, 2008). In addition, variations of the TAM have been created to support
technology acceptance research for a range of technologies such as e-learning (Drennan,
Kennedy, & Pisarski, 2005; Ma & Yuen, 2011), learning management systems (Ngai, Poon, &
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Chan, 2007; Sánchez & Hueros, 2010), and mobile learning (Abu-Al-Aish & Love, 2013; Park,
Nam, & Cha, 2012).
Abu-Al-Aish and Love (2013) developed a modified UTAUT with the intention of
improved prediction of behavioral intention to use m-learning. Their research model identified
the following five constructs as key determiners: (1) performance expectancy, (2) effort
expectancy, (3) social influence (lecturers), (4) quality of service, and (5) personal
innovativeness. One mediating factor was hypothesized – mobile device experience.
The results of Abu-Al-Aish and Love’s (2013) research showed that the five main
constructs of performance expectancy, effort expectancy, social influence, quality of service, and
personal innovativeness were all significant in determining behavioral intention to use mlearning. In addition, mobile device experience had a significant moderating effect on all five of
the main constructs.
Research Purpose and Questions
The purpose of this study was to examine the acceptance and usage of mobile technology
by Japanese university students for informal English-language learning. The following research
questions were addressed in this study:
1. What is Japanese university students’ overall acceptance of the use of mobile devices
for informal English-language learning as measured by a quantitative scale based on
the Technology Acceptance Model (TAM)?
2. What is their actual use of mobile devices for informal English-language learning?
3. What is the relationship between students’ acceptance of mobile devices for informal
English-language learning and their actual use?
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4. Are there any variations in responses based on individual differences?
5. What do students perceive as potential advantages and disadvantages of mobile
devices for informal English-language learning?
Methodology
Setting and Sample
The research study took place in the economics and information science and engineering
departments of a private Japanese university. In 2014, 32,499 students were enrolled at the
university’s four campuses. Students pursuing undergraduate degrees in economics and
information science and engineering are required to complete at least two years of EFL classes
and must achieve a satisfactory score on the Test of English for International Communication
(TOEIC) in order to graduate from their respective programs. While all undergraduate majors in
information science and engineering complete the same English coursework regardless of their
specializations, students in the economics program can choose either a general or international
track. International economics students participate in smaller English communication classes
than those in the general track and have the option of studying a language other than English in
their second year. International economics students tend to be more proficient in English than
those in the general track and are more likely to study abroad.
A sample of economics and information science and engineering students participating in
first- and second-year mandatory English courses was used for this study. One thousand two
hundred and eighteen students enrolled in 59 classes were asked to participate in the study. The
response rate for the study was 80.2%; 977 students completed the survey. Prior to data
83
collection the survey instrument was piloted in two intact business administration EFL classes at
the same university. The response rate for the pilot study was 100%; 48 students responded.
Participants
The majority of participants were male (71.4%); females made up 26.5% of the sample,
while 2.1% preferred not to answer. The participants ranged in age from 18 to 36 (M = 19.03).
Most participants were 18 or 19 years old (73.7%). Students in their first (48.6%) and second
(49.8%) year of study represented the vast majority of the participants; however, 1.6% of the
participants identified their status as either being third-year or as other. Students in the general
economics track represented 41.7% of the sample while 27% were international economics
majors and 31.3% were information science and engineering majors. The participants owned a
variety of mobile devices. Mobile phones were the most common device owned by students
(98.8%), but MP3 players (61.6%) and portable game consoles (51.8%) were also represented.
A smaller percentage of students owned e-book readers (21.1%) and tablets (17.6%).
Instrument
The survey instrument for this study consisted of four sections: (1) acceptance of mobile
devices for informal English-language learning, (2) usage of mobile devices for informal
English-language learning, (3) demographics, and (4) open-ended questions. Section one was an
adaptation of a ML acceptance scale developed by Abu-Al-Aish and Love (2013). The scale was
based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al.,
2003), a variation of the original Technology Acceptance Model (TAM) (Davis, 1989), and
contained 23 items divided into six constructs: (1) performance expectancy, (2) effort
expectancy, (3) lecturers’ influence, (4) quality of service, (5) personal innovativeness, and (6)
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behavioral intention. Reliability coefficients for the original scale exceeded 0.70. A 5-point
Likert scale was utilized in the original scale with the following responses: 1 (strongly disagree),
2 (disagree), 3 (neutral), 4 (agree), and 5 (strongly agree).
After gaining permission to use and modify the scale by the authors, two adaptations
were made to the scale items. First, the original 5-point Likert-scale was converted to a 4-point
scale to address the tendency of Japanese students to choose a neutral response in order to avoid
confrontation (Carless, 2012; Wang, Hempton, Dugan, & Komives, 2008). In addition, changes
were made to reflect the focus of this study on the use of mobile devices for informal language
learning rather than ML in general.
The second section of the survey instrument was a frequency scale measuring students’
usage of mobile devices for informal English-language study. The researcher developed this
measure based on two categorizations of mobile device usage (Cheung & Hew, 2009; Patten,
Arnedillo-Sánchez, & Tangney, 2006), a prior instrument (Santos & Ali, 2011), and the
researcher’s observation and experience. Participants were asked how often they engaged in a
series of informal English-learning activities with a mobile device. Responses were recorded
using a 5-point Likert scale with the responses of 1 (never), 2 (rarely), 3 (occasionally), 4
(frequently), and 5 (very frequently).
The third section of the survey instrument consisted of six demographics questions: (1)
age, (2) gender, (3) academic major (4) class standing, (5) device ownership, and (6) nationality.
Gathering demographic data is especially important in order to ensure that the sample adequately
represents the population to which the results will be generalized (Johnson & Christensen, 2012).
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The final section of the survey consisted of two open-ended questions. The purpose of
these questions was to discover students’ perceptions of the advantages and disadvantages of the
use of mobile devices for the purpose of informal English-language learning.
A native-speaker of Japanese with a high-proficiency in English, as measured by the
TOEIC, translated the instrument. Two additional native Japanese speakers with similar
proficiency in English reviewed the translation and recommended changes. After the instrument
was translated, the researcher conducted a pilot study with two intact classes of students who
were excluded from the actual study. Reliability coefficients were computed for the acceptance
scale following the pilot study. The internal reliability was acceptable (a = .85). After collecting
the data for the actual study, reliability coefficients were calculated again for the acceptance
scale and usage measure. The internal reliability was acceptable for both the acceptance scale (a
= .86) and the usage measure (a = .83).
Data Collection and Analysis
The data were collected during the spring semester of 2015. Nine instructors distributed
a paper-based survey instrument in a total of 59 EFL classes. Participants were provided with
information regarding the study and their rights as research subjects through a letter in Japanese.
Students were instructed to complete the survey outside of class and return it to the instructor in
the following class meeting (one week later).
Five cases that were missing two-thirds or more of the data were eliminated. In addition,
28 participants who did not identify as Japanese or who did not reveal their nationality were
deleted. Frequencies were computed for all items. Missing values were replaced with series
means and z-scores were calculated to identify outliers. Descriptive statistics were calculated for
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the acceptance scale, the six subscales, and the usage measure. A Pearson’s Product Moment
Correlation test was conducted to examine the relationship between acceptance and usage.
Independent t tests and analysis of variance (ANOVA) were used to ascertain whether the
participants’ individual differences affected acceptance. Finally, open-coding was utilized to
analyze responses to open-ended questions. Open-coding data requires the manual sorting of
data into categories, which are created by the researcher (Johnson & Christensen, 2012).
Results and Discussion
Research Question One: Acceptance
Performance expectancy. The majority of participants agreed or strongly agreed that
mobile devices were useful for informal English-language learning (93.8%) and would help them
perform learning tasks more quickly (88.8%). Item 1 had the highest mean score for items on
this subscale (Table 1). Most participants (79.3%) also agreed or strongly agreed that mobile
devices would improve their performance. These results were not surprising because mobile
devices have been shown to be highly effective in a variety of contexts, changing the way we
communicate, play, and learn (Traxler, 2009). Responses were mixed for Item 3 with 56.1% of
students disagreeing or strongly disagreeing and 43.7% agreeing or strongly agreeing that mobile
devices would make them more productive. This may be because mobile devices are often cited
as a distraction that can prevent individuals from putting our full attention to tasks (Goodwin,
2015).
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Table 1
Means and Standard Deviations of Performance Expectancy (PE)
Item
1. I find mobile devices could be useful for informal English language
M
3.18
SD
0.55
3.09
0.59
2.37
0.74
2.85
0.58
learning.
2. Using mobile devices would enable me to complete informal Englishlanguage learning tasks more quickly.
3. Using mobile devices would not increase my informal English-language
learning productivity. [R]
4. Using mobile devices for informal English-language learning would not
improve my performance. [R]
Note. Scale ranging from 1 – strongly disagree to 4 – strongly agree. [R] = reversed item
Effort expectancy. Most participants agreed or strongly agreed with all items in this
subscale. Over 90% of students agreed or strongly agreed with Item 1; this item had the highest
mean score on this subscale (Table 2). Over 80% agreed or strongly agreed with items 6
(84.4%) and 8 (82.1%). The majority of participants agreed or strongly agreed with Item 7
(72.3%). Due to the widespread adoption of mobile devices by Japanese university students as a
primary ICT (Stockwell, 2010; White & Mills, 2014) it was not unanticipated that students
would be familiar with their use and confident that they could handle the devices for the purpose
of learning.
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Table 2
Means and Standard Deviations of Effort Expectancy (EE)
Item
5. I find mobile devices for informal English-language learning flexible and
M
SD
3.13
0.54
3.03
0.63
2.80
0.61
2.98
0.63
easy to use.
6. Learning to operate a mobile device for informal English-language
learning does not require much effort.
7. My interaction with mobile devices for informal English-language
learning would be clear and understandable.
8. It would be easy for me to become skillful at using mobile devices for
informal English-language learning.
Note. Scale ranging from 1 – strongly disagree to 4 – strongly agree.
Lecturers’ influence. The vast majority of students agreed or strongly agreed with Item
9 (90.1%) and Item 10 (88.5%). Item 9 yielded the highest mean score on the LI subscale (Table
3). Most participants disagreed or strongly disagreed that instructors in their department were
not helpful in the use of mobile devices for informal English-language learning (71.4%). The
high level of respect that Japanese culture bestows on teachers could explain these results.
According to Davies and Ikeno (2002), Japanese students still believe that “teachers should be
respected because of their age, experience and ability and what teachers say is always considered
right” (p. 191).
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Table 3
Means and Standard Deviations of Lecturers’ Influence (LI)
Item
9. I would use mobile devices for informal English-language learning if my
M
SD
3.13
0.58
3.10
0.60
2.77
0.63
instructors recommended it to me.
10. I would like to use mobile devices for informal English-language
learning if my instructors supported the use of it.
11. Instructors in my department have not been helpful in the use mobile
devices for informal English-language learning. [R]
Note. Scale ranging from 1 – strongly disagree to 4 – strongly agree. [R] = reversed item
Quality of service. Participants were agreeable with all items in this subscale; all four
items had mean scores above 3.00 (Table 4). Over 90% of students agreed or strongly agreed
that they prefer m-learning services to be accurate and reliable (91.5%) and easy to navigate and
download (94.3%). Over 80% of participants also agreed or strongly agreed that it is important
for m-learning services to increase the quality of learning (88.3%) and focus on speed of Internet
browsing and obtaining information (86.3%). These results were consistent with those of Abu
Al-Aish and Love (2013) who found quality of service to be a significant predictor of students’
acceptance of mobile learning.
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Table 4
Means and Standard Deviations of Quality of Service (QoS)
Item
M
SD
12. It is important for m-learning services to increase the quality of learning.
3.02
0.52
13. I would prefer m-learning services to be accurate and reliable.
3.19
0.59
14. It is important for m-learning to focus on the speed of browsing the
3.04
0.59
3.26
0.57
internet and obtaining information quickly.
15. It is preferable that m-learning services are easy to navigate and
download.
Note. Scale ranging from 1–strongly disagree to 4–strongly agree.
Personal innovativeness. The majority of participants liked to experiment with new
technologies in the classroom (79.3%) and were enthusiastic about examining new technologies
that came to their attention (78.7%). However, many students were reluctant to identify
themselves as early adopters of new technology among their peers (61.9%). One explanation for
the low mean score (2.34) (see Table 5) is that the Japanese are a highly collective culture where
conformity is considered a desirable quality (Hofstede, Hofstede, & Minikov, 2010); therefore,
students may have been averse to labeling themselves as early adopters because it would set
them apart from their peers.
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Table 5
Means and Standard Deviations of Personal Innovativeness (PInn)
Item
M
SD
16. I like to experiment with new information technologies.
3.02
0.72
17. When I hear about a new information technology I look forward to
2.99
0.70
2.34
0.79
examining it.
18. Among my peers, I am usually the first to try out a new innovation in
technology.
Note. Scale ranging from 1–strongly disagree to 4–strongly agree.
Behavioral intention. Many participants thought they would enjoy using mobile devices
for informal English-language learning (79.1%) and planned to use mobile devices for this
purpose (77.2%). Over 60% of students predicted they would use mobile devices frequently for
informal English-language learning (67.1%) and intended to increase their use of mobile devices
for informal learning (69.6%). Only 68.0% would recommend their peers to utilize mobile
devices for informal English-language learning (M = 2.74) (Table 6). These results seem to
show that participants are open to utilizing their personal mobile devices for informal Englishlanguage learning but still have some concerns regarding the practice. However, they may be
less concerned with issues such as privacy and separating educational activities and their
personal lives which were barriers identified in previous MALL research in Japan (Kondo et al.,
2012; Stockwell, 2008, 2010).
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Table 6
Means and Standard Deviations of Behavioral Intention (BI)
Item
M
SD
19. I plan to use mobile devices for informal English-language learning.
2.86
0.59
20. I predict that I will use mobile devices for informal English-language
2.75
0.67
2.77
0.64
2.89
0.61
2.74
0.67
learning frequently.
21. I intend to increase my use of mobile devices for informal Englishlanguage learning in the future.
22. I will enjoy using mobile devices for informal English-language
learning.
23. I would recommend others to use mobile devices for informal Englishlanguage learning.
Note. Scale ranging from 1–strongly disagree to 4–strongly agree.
In general, participants were open to the use of mobile devices for the purpose of
English-language learning. The subscale quality of service had the highest mean score; whereas
personal innovativeness had the lowest mean score (Table 7).
Table 7
Means and Standard Deviations of Acceptance Scale and Subscales
Scale
M
SD
Total
2.93
0.31
Performance Expectancy
2.87
0.34
Effort Expectancy
2.99
0.44
Lecturer Influence
3.00
0.43
Quality of Service
3.13
0.39
Personal Innovativeness
2.79
0.61
Behavioral Intention
2.80
0.52
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Research Question Two: Actual Usage
Respondents engaged in informal English-language learning using their mobile devices
for 0 to 90 hours per week (M = 2.33, SD = 5.37). However, the median number of hours that
students participated in informal MALL was only one hour per week. When using their mobile
devices for this purpose, a slight majority of respondents reported that they were conscious of
participating in learning activities (58.6%), whereas the others were not conscious that learning
was taking place (41.4%).
Participants were asked what mobile devices they used to engage in informal Englishlanguage learning. Students reported using mobile phones most often, followed by MP3 players,
and portable game consoles. Tablet computers and e-book readers were used the least for
informal English-language learning. These results correspond roughly with the ranking of access
to these devices among the Japanese populace provide by the Ministry of Internal Affairs and
Communication (2014a). They reported that Japanese own the following devices: (1) mobile
phones (94.8%), (2) smartphones (62.6%), (3) portable games consoles (38.3%), MP3 players
(23.8%), tablet computers (21.9%), and other internet enabled devices (8.8%).
Participants were also questioned about the informal English-language learning activities
in which they engaged. The highest mean scores were recorded for Items 31, 35, and 36 (Table
8). Over 70% of students responded that they listened to music or accessed a translation
application very frequently, frequently, or occasionally. More than 80% of students reported
using dictionary applications with the same frequency. The activities which students engaged in
the least were associated with Items 28 (social networking sites), 30 (games), and 38 (news).
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It was surprising that social networking sites and games were underrepresented in this
sample. In 2013, over 60% of Japanese young people utilized social networking sites (Ministry
of Internal Affairs and Communications, 2014), and they are gaining popularity every year.
Japan is a primary consumer of mobile games for the iPhone (Warman, 2013), and on average,
residents of the country engage in mobile game play for 190.8 minutes a day (Ministry of
Internal Affairs and Communications, 2014). These data seem to indicate that while Japanese
young people are using these applications in their native language, they are reluctant to do so in
English.
Table 8
Uses of Mobile Devices for Informal English Language Learning
Response (Percent)
Item
N
R
O
F
V
27. English-language websites.
19.6
28.6
38.3
11.3
2.1
28. English-language social
40.3
28.5
23.1
6.2
1.6
25.0
24.2
36.0
11.9
2.3
30. English-language games.
42.4
24.2
23.1
8.1
1.9
31. English-language music.
7.8
13.6
31.6
26.7
19.6
32. English-language spoken
28.5
27.3
30.0
9.4
4.2
13.4
20.7
35.7
21.3
8.7
16.3
24.1
32.6
19.0
7.5
6.6
12.4
27.8
38.1
14.4
networking sites.
29. English-language learning
applications.
audio (i.e. podcasts).
33. English-language videos
(i.e. YouTube).
34. English-language TV shows
or movies.
35. Dictionary applications.
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36. Translation applications.
8.3
18.5
29.1
32.2
11.7
37. English-language e-books.
37.8
19.4
17.2
15.9
9.5
38. English-language news.
37.7
33.5
20.3
6.1
1.9
Note. Scale items: N = Never, R = Rarely, O = Occasionally, F = Frequently, V = Very
Frequently
Research Question Three: Relationship Between Acceptance and Usage
Correlation coefficients were computed between the acceptance scales (total and subscales) and the total usage measure. In order to control for Type I errors, the Bonferroni
approach was employed requiring a p value of less than .005 (.05/10 = .005). Each of the six
subscales of acceptance, as well as the total scale, was significantly correlated with the usage
measure (Table 9). However, only the behavioral intention subscale and the total acceptance
scale were correlated with the usage measure at or above .30. These results suggest that the
technology acceptance model is a reliable predictor of actual usage in the context to which it was
applied in this study; however, the total scale and behavioral intention were the most significant
determiners of the model.
Table 9
Correlations Between Acceptance and Usage Scales
Acceptance Scales
Usage Scale
Performance Expectancy (PE)
.117*
Effort Expectancy (EE)
.231*
Lecturers’ Influence (LI)
.214*
Quality of Service (QoS)
.131*
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Personal Innovativeness (Pinn)
.299*
Behavioral Intention (BI)
.423*
Total Scale
.374*
Note. *p < .005
Correlation coefficients were also calculated between the acceptance scales and
participants reported use of mobile devices for informal English-language learning. The results
of this analysis showed that the correlation between the total acceptance scale and mobile device
usage was significant, r(926) = .131, p = .000. The subscales of behavioral intention, r(926) =
.148, p = .000 and personal innovativeness, r(926) = .131, p = .000, were also significantly
correlated with mobile device use. However, it is important to note that the coefficients were
small in each of these cases. A possible explanation for this is that technology acceptance is only
one of several factors that determine usage of mobile devices for informal English-language
learning. Further research will need to be conducted in order to ascertain which additional
factors are predictive with the subjects in this study.
Research Question Four: Individual Differences
Several analyses were conducted in order to examine the influence that individual
differences such as gender, purpose, and academic major had on the acceptance and usage of
mobile devices for informal English-language learning.
Gender. Independent t tests were computed to ascertain differences in acceptance and
usage among men and women. The results of these analyses showed that the responses of males
and females were significantly different in the performance expectancy t(925) = -2.06, p = .040
and personal innovativeness subscales t(925) = 6.02, p = .000. Women had a significantly higher
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mean score in performance expectancy (M = 2.91) than men (M = 2.86). However, male
participants (M = 2.85) had a statistically higher mean score in personal innovativeness than
female participants (M = 2.58). There was no statistically significant difference between the
genders in the other acceptance subscales or in terms of the usage measure.
Gender was an important consideration in the context being studied because previous
research showed that while mobile internet usage was similar between men and women mobile
phones often functioned as the primary ICT used by women in Japan (Akiyoshi & Ono, 2008).
Therefore, it is understandable that women would hold different expectations than men towards
these devices.
Purpose. Independent t tests were performed to examine differences in acceptance and
usage of participants who reported to mainly engage in informal MALL consciously versus those
who did so unconsciously. Significant differences were found between the two groups in their
responses to the effort expectancy t(882) = -2.34, p = .019 and personal innovativeness subscales
t(882) = -2.86, p = .004. Individuals who mainly practiced informal English-language learning
unconsciously were significantly higher in effort expectancy and personal innovativeness (M
=3.02, 2.85), than those who were conscious of their learning (M = 2.95, 2.74).
There was also a statistically significant difference between these two groups in terms of
their usage of mobile devices t(871) = -3.04, p = .002. Respondents who claimed to be mostly
unconscious of their informal English-language learning had a higher mean score (M = 1.86)
than those who were conscious of the process (M = 1.68). One explanation for these results is
that students engaging in unconscious informal language learning are more relaxed, which
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reduces their perceptions of effort and makes them more likely to experiment with the
technology to which they have access.
Academic Major. A one-way analysis of variance (ANOVA) test was computed to
determine differences in acceptance and usage among participants based on their academic
major. Significant differences were discovered on the performance expectancy, F(2, 944) = 4.28,
p = .014, lecturers’ influence, F(2, 944) = 4.50, p = .011, personal innovativeness, F(2, 944) =
6.73, p = .001, and behavioral intention scales, F(2, 944) = 3.80, p = .023, as well as the usage
measure, F(2, 944) = 6.03, p = .003.
Follow-up tests were conducted to examine the pairwise differences among the means. A
Levene’s Test of Equal Variances was computed and the results showed that variances were
homogeneous for personal innovativeness, behavioral intention, and the usage measure.
However, variances were not homogeneous for performance expectancy and lecturers’ influence.
This may suggest that the participants provided more consistent responses to items related to
constructs, which were objective and controllable. In contrast, they were less consistent with
responses concerning constructs that were subjective and required introspection. The Tukey
HSD was used for the subscales and measure with equal variance and the Dunnett C was used
for the subscales with unequal variance.
The results of a Dunnett C test showed that there was a significant difference in mean
scores related to performance expectancy between economics (M = 2.84) and international
economics majors (M = 2.92). In addition, international economics majors (M = 3.07) seem to
be more influenced by their lecturers than students in the standard economics program (M =
2.98) or the information science and engineering program (M = 2.97). These results might be
99
explained by the fact that international economics students enjoy smaller class sizes in their
required English classes, which could lead to closer relationships with their teachers and create a
classroom culture that is more dependent on lecturers’ approval.
Tukey HSD post hoc tests revealed that information science and engineering students (M
= 2.89) displayed greater personal innovativeness in their use of mobile technology that either
economics (M = 2.74) or international economics students (M = 2.72). This is understandable
because information science and engineering students, due to their area of study, are more likely
to come into contact with new information and communication technology and have personal
and professional reasons to experiment with its use. In regards to behavioral intention, a followup test (Tukey HSD) revealed that international economics majors had significantly higher mean
scores (M = 2.85) than information science and engineering majors (M = 2.74). This result is not
unforeseen because students in the international economics track tend to have a greater interest in
improving their English language skills and will therefore be more likely to make use of any
opportunity or technology that could assist them in this goal. This is because these students
choose to take part in the international economics program at a greater cost in both time and
money than the students in the standard program. These factors lead to a self-selection bias,
which tends to increase the number of students who possess an international posture and display
higher motivation to study English.
Finally, the results of a Tukey HSD post hoc test revealed significant differences in the
means associated with the usage measure between international economics majors (M = 2.73) in
comparison to economics (M = 2.59) and information science and engineering majors (M =
2.54). This is probably because international economics majors, as stated earlier, are more likely
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than students majoring in other subjects to have a keen interest in improving their English ability,
which they see as paramount to pursuing future careers in global commerce and industry.
Research Question Five: Perceived Advantages and Disadvantages
Advantages. Seven hundred and fifty-eight participants offered their opinion regarding
their perceived advantages of the use of mobile devices for informal English-language learning.
Only eleven students responded that they had no comment on the matter or did not know. The
remaining comments were categorized into five elements (Table 10).
Table 10
Number of Comments Coded as Identified Elements Representing Perceived Advantages
Elements of Perceived Advantages
Number of Comments
Percent
210
28.1
40
5.4
Convenience/Access
354
47.4
Ease of Use
118
15.8
Enjoyment
25
3.3
Learning/Studying
Information
Most responses focused on the convenience and accessibility of mobile devices for
learners. Students wrote that the portability of mobile devices allowed them to participate in
language study at any time or place. In particular, many participants mentioned the advantage of
being able to study when commuting on public transportation. The ability to use mobile devices
to learn anywhere and at any time is often cited in the literature as a key affordance of ML
(Kukulska-Hulme, 2013; Viberg & Grönlund, 2012).
Participants also commented on the advantages of learning and studying with mobile
devices. Students perceived that mobile devices would increase the efficiency and effectiveness
101
of learning. One reason for this is that mobile devices allowed them to learn using a variety of
media such as video and audio. For example, one student wrote, “I can practice listening easily.
It is impossible to practice listening skills by paper-based material, or it might take some time to
get started with a CD-ROM, so people might not do it.”
Many students also cited ease of use as a perceived advantage of informal mobile
learning. These responses confirm the quantitative data collected through the survey instrument
regarding effort expectance and were not surprising because most of the participants own at least
one mobile device.
The remainder of the comments pertained to the amount and variety of information that
participants could access on their mobile devices as well as the perceived enjoyment they would
experience when engaging in informal mobile learning.
Disadvantages. Students were also invited to share their thoughts on the potential
disadvantages of using mobile devices for informal English-language learning. Six hundred and
ninety-four students responded to the question. Seventy-eight students wrote that they did not
know or they had no comment. The remaining responses were categorized into six elements
(Table 11).
102
Table 11
Number of Comments Coded as Identified Elements Representing Perceived Disadvantages
Elements of Perceived Disadvantages
Number of Comments
Percent
319
51.8
Security
26
4.2
Accuracy
49
8.0
Health Concerns
78
12.7
110
17.9
34
5.5
Learning/Studying
Device
Communication
Despite the positive comments students expressed regarding learning and studying with
mobile devices, they identified several disadvantages. Distraction was one perceived
disadvantage of the use of mobile devices for learning. Students also seemed to be worried that
without actually writing down information they were studying with a pencil and paper, they
would not be able to memorize it. In addition, respondents wrote that their overall learning
ability might decrease because mobile devices made learning “too easy” and would not allow
them to “think on their own.”
Issues related to the device and access to service were also cited as potential
disadvantages. Some of the concerns in this category were the cost, battery life, fragility, and
lack of access to Wi-Fi. Access to Wi-Fi is surprising to many people who are not familiar with
Japan because the country is often associated with technological innovation. However, free WiFi access is still limited in Japan (Nagata, 2015), making this a real concern for students who
wish to take advantage of the portability of mobile technology for learning.
103
Participants were very worried about the negative effect that the use of mobile devices
could have on their bodies and minds. Many respondents wrote that using digital technology
could have a detrimental impact on their eyesight, and some were concerned that they may even
become addicted to the devices. These comments were not surprising because Japanese people,
of all ages, tend to be very concerned about their health. This concern has contributed to Japan
having the highest life expectancy in the world for men and the second highest for women
(World Health Organization, 2014).
The remaining comments were concerned with security of personal information, the
accuracy of information obtained from the Internet, and the worry that mobile learning might
reduce communication with both peers and teachers. All of these concerns are legitimate and
need to be addressed by teachers and administrators implementing mobile learning programs at
their institutions.
Conclusion
The purpose of this study was to investigate acceptance and usage of mobile devices for
informal English-language learning among Japanese university students. The results showed
that, overall, participants were accepting of the use of mobile devices for this purpose and
already engaging in a variety of informal MALL activities. Students saw mobile devices as
beneficial to their learning and were enthusiastic about the prospect of engaging in language
study in any time or place. In addition, they saw the devices as easy to use due to their
experience and envisioned mobile study as enjoyable.
Nevertheless, participants also had concerns with the negative effects of mobile learning.
A large number of respondents were worried about distraction from study, and many saw
104
learning with the devices as detrimental to their physical and mental health. Finally, they were
unsure that mobile learning was as effective as traditional methods in increasing their proficiency
in English.
There were several limitations to the study that need to be addressed. First, the data was
collected from one selective, private university in Japan. For this reason, students might have
been more proficient academically and of a higher socioeconomic status than their counterparts
at other universities throughout the country. Therefore, future research in Japan would benefit
from using a more diverse sample. In addition, because the researcher collected data in his
classes, there is a chance of investigator bias (Gravetter & Forzano, 2009) as well as concerns
regarding the effects of power and influence on the results (Creswell, 2014). These issues might
be exacerbated due to Japanese cultural factors, which places superiors, such as teachers, into
higher power positions.
While the results of this study provide researchers with a general overview of informal
English-language learning using mobile devices in the Japanese university context, there are a
number of specific areas of study that should be addressed in future research. For example, the
current study did not examine the effect of informal MALL on English proficiency. This might
be an important area of future study considering the concerns expressed by students regarding
the effectiveness of digital devices for the purpose of language learning. Furthermore, more
accurate data regarding informal learning activities could be obtained if participants were asked
to keep a daily diary recording their usage of mobile devices rather than relying on a selfreported scale. Finally, adding a qualitative component to future studies may provide researchers
105
with a greater depth of information regarding the subject of informal MALL and triangulate the
quantitative results in the current study.
106
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Chapter 5: Implications, Recommendations, Limitations, and Future Research
Implications
The results of this research study will be beneficial to educators, researchers, and
administrators in Japanese universities as well as to companies that supply mobile technology
and applications for the Japanese market. For instructors, discovering how students are using
their mobile devices to learn English informally will increase understanding of the learning
activities and applications with which students engage outside of the formal classroom setting.
Furthermore, instructors will discover which devices are most favored by students for informal
English learning. This information could be used to develop prescribed activities related to the
interests of learners, and provide knowledge of the applications and devices with which students
are most familiar. This is an important consideration because today’s university students are
often considered “digital natives,” a term coined by Prensky (2001) to denote individuals who
have grown up with technology, and therefore are comfortable with its use. However, research
has shown that young people often do not have the knowledge of how to use technology for
specific purposes, such as learning, despite their reputation as digital natives (Bennett, Maton, &
Kervin, 2008; Thomas, 2011). Abdous, Camarena, and Facer (2009) and Stockwell (2008)
found in their studies of podcasting and vocabulary learning that many university students did
not utilize the technology in the study because they were not confident in its use. Therefore, it
would be erroneous for educators to assume that learners will automatically know how to use a
technology without adequate training (Stockwell, 2012b). Finally, knowledge of various factors
that affect students’ acceptance of mobile devices can provide educators with an understanding
of the affordances and challenges presented by these devices, and educators can utilize this
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information in their implementation of the technology in the classroom. For example, a
construct of acceptance in the Technology Acceptance Model (TAM) is perceived usefulness.
Research conducted by Stockwell (2008, 2010) showed that Japanese university students did not
view their personal mobile devices as appropriate for educational use. However, social
influence, especially from educators, can also affect acceptance (Abu-Al-Aish & Love, 2013).
Therefore, it may be possible for an instructor to reduce the negative perceptions of a technology
by the promotion of it in her or his class.
University administrators can also make use of the results of this study. While educators
most often set policies for use of mobile devices in their individual classrooms and can
encourage their informal use outside of the class setting, administrators are involved with
providing support services and can also make decisions regarding the adoption of new
technologies. In Nagoya Bunri University, for example, iPads are distributed to all students once
they begin their studies and both learners and teachers are encouraged to use the devices for
educational purposes. The devices are used in a number of ways to facilitate communication
through social networking sites and also to move towards a paperless classroom environment
(Hasegawa, Yasui, & Yamaguchi, 2013).
For researchers, a critical gap exists in the literature regarding informal learning with
mobile devices for the purpose of language learning. Several researchers (i.e., Santos & Ali,
2011; Cheung & Hew, 2009) have explored the usage of mobile devices for informal learning,
but few studies exist that examine usage in the informal mobile-assisted language learning
(MALL) context. The majority of this research focuses on bridging formal and informal learning
rather than examining usage in a completely naturalistic setting. For this reason, the current
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study provides researchers with a breadth of data concerning usage and acceptance of mobile
technology for informal language learning in Japan that could be the basis for future research.
Finally, the data from this study could be applied to the marketing and design of mobile
technology and applications. Japan has a high mobile phone penetration rate. Of an
approximate population of 123 million, 94% own a mobile device (Ministry of Internal Affairs &
Communication, 2014a). In addition, since 2013, Japan had the highest consumer spending on
mobile device applications in the world (Negeshi, 2013). With such a large market and the need
of this market to acquire English language proficiency, the results of this study will be important
for the producers of mobile hardware and software. While sales data provides application
designers with information regarding usage, data from this study might alert designers to novel
uses of applications. For example, Barrs (2011) showed that students often used their camera
application to take pictures of notes on the white or blackboard. This unintended usage by
students all over the world prompted designers to develop specific applications to meet this need,
such as Whiteboard Share (Ricoh, 2016). Furthermore, data regarding user perceptions could
lead to changes in mobile technology hardware design. Perceived ease of use is a construct of
the TAM that directly influences behavioral intention to use a particular technology. If
participants indicate that a certain mobile device is difficult to use and is therefore preventing its
utilization for informal learning, mobile technology companies could use this information to
address the problem, and through further research discover a solution.
Recommendations
There are several recommendations that can be made to individuals and organizations
involved with English education in the Japanese context based on the findings of this study.
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First, the researcher discovered that there was a direct, positive correlation between the five
constructs of technology acceptance and students’ usage of personal mobile devices for informal
language learning. Therefore, individuals and organizations that wish to increase the practice of
informal MALL among Japanese university students must strive to make students more
accepting of this practice.
There are several ways that student perceptions of performance expectancy and effort
expectancy can be influenced. For example, stakeholders should explain to students the benefits
of using mobile devices for informal language learning, and provide adequate support for the use
of mobile devices for this purpose. In addition, if educators effectively integrate mobile learning
into classroom activities, learners will come to appreciate the effectiveness of the paradigm and
become more proficient at using mobile technology in this context. Furthermore, because
lecturers’ influence was correlated with increased usage in this study, it is important for
universities who wish to increase student engagement in informal MALL to ensure that
educators support the plan if it is to be successful.
Although at first glance it seems that quality of service and personal innovativeness are
factors for which it is more difficult to have a direct influence, there are several ways that
universities could seek to increase perceptions of these constructs among students. First, a
reliable wireless Internet network is essential for students to engage in technology for teaching
and learning. Universities should strive to provide the best services available to support students
and faculty in their use of technology for learning. In addition, the results of this study show that
quality of service is an essential influencer of usage and therefore should be a priority for
developers of learning applications. Moreover, educators can impact students’ perceptions of
119
personal innovativeness through the activities and tasks they employ in the classroom. By
engaging learners using an active, student-centered approach and exposing them to a variety of
technologies, educators can influence students’ view of themselves as innovators.
Finally, individuals and organizations interested in promoting informal MALL in Japan
should use the data in this study to design and implement more effective mobile learning
activities and applications. The results of the research showed that while students are using their
mobile devices for informal language learning, they are mostly doing so for passive learning
activities such as the use of dictionary applications and to listen to music. However, one of the
main benefits from technology enhanced language learning is that it provides a platform with
which students can connect and communicate with native speakers and other learners of English
around the world. Therefore, in addition to utilizing the data from this study to develop
applications that cater specifically to current learning habits, it would be highly beneficial if
applications were created that facilitated interaction in the target language.
Limitations
Despite every effort being made by the researcher to ensure that the methodology of the
study was sound, there were several limitations to the current study. For example, data was
gathered from only one private university in western Japan. In addition, students from only two
academic departments, economics and information science and technology, participated in the
research.
The setting for this research project was a selective institution, which is one of the top
five private universities in the region. Because it is a private university, the tuition fees are
almost double of those at public universities in the region. Furthermore, many of the students at
120
the university which was used as the setting of the study, have attended the school’s affiliated
primary and secondary schools, where the tuition is also high. This could indicate that students
at this university have a higher socio-economic status than those at public universities or private
schools with lower tuition rates. In addition, socioeconomic/class differences might exist
between learners within the university who are attending on scholarships rather than through
familial support. Because socio-economic status is a determining factor of ICT usage in Japan
(Akiyoshi & Ono, 2008), the results of this study are limited in that data was only collected from
this one private university.
In addition to the limitation of socio-economic status, the participants for the study were
drawn from only two departments and only among undergraduate students. As the results of the
study suggest, differences in responses exist between students in the economics and information
science and technology departments, so we can only assume that further differences would be
discovered if other departments were included. Furthermore, because the sample was drawn
only from first- and second-year undergraduate students, the majority of participants were
between the ages of 18 to 20. This limitation did not allow the researcher to fully explore
differences in responses to acceptance and usage that might be present due to age.
Another important limitation of the study was due to the method of data collection.
Because course instructors delivered the survey instrument in their classes, there is the possibility
that participants may have felt pressured to complete the survey, and responded in a way that
they imagined would by preferred by their instructor. This may be especially relevant because
the study took place in Japan. Japanese culture operates in a hierarchal structure where the
relationship between inferiors and superiors is very important (Davies & Ikeno, 2002). In
121
particular, teachers are highly revered in Japanese society (Davies & Ikeno, 2002), which may
have influenced the results of the study.
Finally, the data gathered for this study regarding acceptance and usage was all selfreported. Several studies have shown that self-reported data may not be accurate representations
of reality (Barker, Pistrang, & Elliott, 2015; Stockwell, 2012a). However, alternatives to selfreported data, such as having students use devices or applications provided by the researcher that
monitored usage would have defeated the purpose of the study, which was to ascertain how
students used their personal mobile devices for the informal language study without interference
from the researcher.
Future Research
Both the results and the limitations of this study, provide ample opportunities for future
research. The purpose of this research project was to gain a general understanding of students’
acceptance and usage of their personal mobile devices for informal English-language learning.
However, the current study did not examine the effect of informal mobile learning on English
proficiency. Future research could utilize a number of assessments of English language skills,
including standardized tests, projects, and presentations, to examine the correlation between
informal mobile language learning and proficiency. In the setting of the current study, students
take the Test of English for International Communication (TOEIC) exam before each scholastic
year to place them in the appropriate level of class. While individual scores are not available to
instructors and/or researchers, a modified survey instrument could ask students to self-report the
information.
122
Furthermore, adding a qualitative component to future studies may provide researchers
with a greater depth of information regarding the subject of informal MALL and triangulate the
quantitative results in the current study. For example, more accurate data regarding informal
learning activities could be obtained if participants were asked to keep a daily diary recording
their usage of mobile devices rather than relying on a self-reported scale. Moreover, focus
groups or semi-structured interviews with individual students would allow researchers to explore
more fully the positive and negative issues identified by participants in the open-ended questions
and to extrapolate on the specific ways students are using their mobile devices for informal
MALL.
Finally, as pointed out in the limitations section of this chapter, the participants of the
study were drawn from one private university in western Japan. Future research would benefit
greatly from a more diverse sample of higher education students than those sampled in this
investigation. In particular, it would be informative to see how socio-economic status affects
mobile device access and usage. In addition, since the setting used for this study is a selective
university in Japan, including lower proficiency learners would add an interesting component to
future research. This would allow the researchers to explore several factors including the effect
of English ability, academic prowess, motivation, and self-efficacy on the adoption of informal
MALL. Lastly, to gain an even greater understanding of how students are using their mobile
devices for English language study, research could be conducted in other countries. The
Japanese culture plays a unique role in the acceptance and usage of technology for educational
purposes (Aoki, 2010; Latchem et al., 2008; Lockley, 2011; Murray & Blyth, 2011); therefore, it
123
would be interesting to see how students from an alternative culture might use or accept informal
MALL differently.
Conclusion
University students in Japan face a difficult road ahead due to the economic and societal
woes of their country. Japan has yet to recover from the recession it entered after the economic
bubble burst in the 1990s, and because of a low birth rate and a long life span, the country’s
pension system is facing collapse. For Japan to thrive, let alone survive, in the coming decades,
companies will need to seek business oversees and the country will have to reform immigration
policies which will affect the cultural and language diversity of the country. In both cases,
English language skills will be essential for the citizens of this unique island nation.
Formal and nonformal English language education has long been a required part of the
educational system in Japan, but competence in the language remains low among most Japanese
people (Sakamoto, 2012). This is due to a variety of factors including a rigorous testing system
that placed an emphasis on the memorization of grammar and vocabulary over communicative
practice (Yashima & Zenuk-Nishide, 2004), and cultural factors that might contribute to a low
willingness to communicate among learners (Freiermuth & Jarrell, 2006). However, because of
the high penetration rate of mobile technology, and the opportunities it affords learners in terms
of content and flexibility, many of the obstacles to second language acquisition (SLA) in Japan
can be reduced, or in some cases, eliminated (Stockwell & Hubbard, 2013).
Through this research it was determined that the subjects in this study were open to the
possibility of engaging in informal MALL and were using their personal devices in a variety of
ways for this purpose. In particular, students surveyed in the study were utilizing their mobile
124
phones to listen to English-language music, and to access English dictionaries and translation
software. While these results were promising, the study revealed that students were not taking
advantage of many Web 2.0 technologies that could be effective in developing their
communicative skills by connecting them with native speakers and advanced learners of English.
In addition, while the participants of the research identified several advantages of mobile
learning such as access to educational content at any time and place, they were undecided
regarding the effectiveness of mobile devices to provide real learning opportunities and were
concerned about the negative effects technology use might have on their health.
Based on the research data, it is recommended that individuals and organizations that are
eager to promote the use of informal MALL in Japan seek to improve students’ acceptance of
this practice first. In additional, current preferences and usage should be taken into account not
only to develop more effective applications and learning tasks for students, but also to identify
how the devices might be used more effectively by students and create interventions to influence
desired outcomes.
Finally, the data from this study should be used as a springboard from which to launch
additional inquiries that address the shortcomings of this project, as well as explore areas of
interest highlighted in the investigation. For example, while data regarding usage and
acceptance is a necessary first step in our understanding of informal MALL, we must also study
how this practice affects language acquisition. Moreover, the setting and participants in the
study were limited, and future research would benefit from a more diverse sample of subjects
that would allow researchers to better understand the influence of socio-economic status, English
125
proficiency, academic ability, motivation and self-efficacy on the use and acceptance of informal
MALL.
126
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155
Appendix A: Survey instrument (English)
Acceptance and Usage of Mobile Devices for Informal English Language Learning
ACCEPTANCE
Instructions: Please read the questions below carefully and indicate your level of agreement by
checking one response for each question.
Strongly
Disagree
1
I find mobile devices to be useful for informal Englishlanguage learning.
2
Using mobile devices would enable me to complete
informal English-language learning tasks more quickly.
3
Using mobile devices would not increase my informal
English-language learning productivity.
4
Mobile learning could improve my collaboration with
classmates.
5
Using mobile devices for informal English-language
learning would not improve my performance.
6
I find mobile devices for informal English-language
learning flexible and easy to use.
7
Learning to operate a mobile device for informal Englishlanguage learning does not require much effort.
8
My interaction with mobile devices for informal Englishlanguage learning would be clear and understandable.
9
It would be easy for me to become skillful at using
mobile devices for informal English-language learning.
10
I would use mobile devices for informal Englishlanguage learning if my instructors recommended it to
me.
11
I would like to use mobile devices for informal Englishlanguage learning if my instructors supported the use of
it.
156
Disagree
Agree
Strongly
Agree
Strongly
Disagree
12
Instructors in my department have not been helpful in
the use mobile devices for informal English-language
learning.
13
It is important for m-learning services to increase the
quality of learning.
14
I would prefer m-learning services to be accurate and
reliable.
15
It is not important for m-learning services to be
secure to use.
16
It is important for m-learning to focus on the speed of
browsing the internet and obtaining information
quickly.
17
Communication and feedback between lecturers and
students would not be easy using m-learning
systems.
18
It is preferable that m-learning services are easy to
navigate and download.
19
I like to experiment with new information
technologies.
20
When I hear about a new information technology I
look forward to examining it.
21
Among my peers, I am usually the first to try out a
new innovation in technology.
22
I plan to use mobile devices for informal Englishlanguage learning.
23
I predict that I will use mobile devices for informal
English-language learning frequently.
24
I intend to increase my use of mobile devices for
informal English-language learning in the future.
25
I will enjoy using mobile devices for informal Englishlanguage learning.
26
I would recommend others to use mobile devices for
informal English-language learning.
157
Disagree
Agree
Strongly
Agree
USAGE
Instructions: Please read the questions below carefully and indicate your level of use by
selecting your response or filling in your answers.
When using a mobile device for informal English-language learning how often do you employ
the following?
Never
Rarely
27 English-language websites
28
English-language social networking
sites
29 English-language learning applications
30 English-language games
31 English-language music
32
English-language spoken audio (i.e.,
podcasts)
33 English-language videos (i.e. YouTube)
34 English-language TV shows or movies
35 Dictionary applications
36 Translation applications
37 English-language e-books
38 English-language news
39 Other (Please write in your answer)
158
Occasionally
Frequently
Very Frequently
40. I use the following for informal English-language learning (mark all that apply).
a.____ Mobile phone or smartphone
b.____ MP3 Player (i.e., iPod Nano or Walkman)
c.____ E-book reader (i.e., Kindle or Kobo)
d.____ Tablet computer (i.e., iPad or Galaxy Tab)
e.____ Handheld game console (i.e., Nintendo DS or PSP)
f.____ Other (please write your answer here) __________________________
41. On average, how many hours per week do you use mobile devices for informal English
language learning? ________ hours
42. When using a mobile device for informal English study, I primarily … (mark only one)
a.____ do it for the purpose of learning.
b____ do it without realizing I am engaged in a learning activity.
DEMOGRAPHICS
Instructions: Please fill in your answer.
43. What is your age? ________ years
44. What is your nationality? ________________________________________
Instructions: Please complete the following questions by selecting one answer.
45. What is your gender?
a.___ Male
b.___ Female
c.___ Prefer not to answer
46. What is your academic major?
a.___ Economics
159
b.___ International Economics
c.___ Information Science
d.___ Other (please write your answer here): __________________________
47. What is your academic standing?
a.___ First-year student
b.___ Second-year student
c.___ Third-year student
d.___ Fourth-year student
e.___ Other: Please explain _______________________________________
48. I own the following mobile devices (mark all that apply).
a.___ Mobile phone or smartphone
b.___ MP3 Player (i.e., iPod Nano or Walkman)
c.___ E-book reader (i.e., Kindle or Kobo)
d.___ Tablet computer (i.e., iPad or Galaxy Tab)
e.___ Handheld game console (i.e., Nintendo DS or PSP)
f.___ Other (please write your answer here): ____________________________
OPEN-ENDED QUESTIONS
Instructions: Please complete the following questions by writing in the answer.
49.What are the advantage(s) for using mobile devices for informal English-language learning?
____________________________________________________________________________
____________________________________________________________________________
____________________________________________________________________________
160
50.What are the disadvantage(s) for using mobile devices for informal English-language
learning?
____________________________________________________________________________
____________________________________________________________________________
____________________________________________________________________________
161
Appendix B: Permission Letter
162
Appendix C: Survey Instrument (Japanese)
受容 下記の質問をよく読み、あなたの意見に該当する欄１つにチェックを入れてください。 まったく
そう思わ
ない そう思
わない そう思う 非常にそ
う思う 1 モバイル機器はインフォーマル英語学習に便
利だ。 2 モバイル機器を使うことでインフォーマル英
語学習のタスクをより早く完了することがで
きる。 モバイル機器を使うことはインフォーマル英
語学習の生産性を向上させない。 3 モバイル学習はクラスメイトとのコラボレー
ションを高める。 4 5 インフォーマル英語学習にモバイル機器を使
うことは私のパフォーマンスを向上させな
い。 6 インフォーマル英語学習のためにモバイル機
器使うことは柔軟性があり使いやすい。 7 インフォーマル英語学習のためにモバイル機
器の操作方法を学ぶことはそれほど苦労がい
らない。 インフォーマル英語学習のために使うモバイ
ル機器と私の相互関係は明確で理解できる。 8 9 インフォーマル英語学習のためにモバイル機
器をうまく使えるようになることは簡単だと
思う。 10 もし先生から薦められたら、インフォーマル
英語学習のためにモバイル機器を使うと思
う。 もし先生が使い方のサポートをしてくれたら
インフォーマル英語学習のためにモバイル機
器を使うと思う。 11 まったく
163
そう思
そう思う 非常にそ
そう思わ
ない わない う思う 12 私の学部の先生はインフォーマル英語学習の
ためにモバイル機器を使うことについて助け
になっていない。 13 モバイル学習サービスにとって学習の質を向
上させることは重要である。 モバイル学習サービスが正確で信頼性がある
ようになってほしいと思う。 14 モバイル学習サービスが安全に使えることは
重要ではない。 15 16 モバイル学習にとってインターネット閲覧の
スピードやすばやく情報を得られることに焦
点をあてることは重要である。 17 モバイル学習システムを使った先生と学生の
間のコミュニケーションやフィードバックは
簡単ではない。 モバイル学習サービスのナビゲーションやダ
ウンロードは簡単であることが望ましい。 18 新しい情報テクノロジーを試してみることが
好きだ。 19 新しい情報テクノロジーについて聞いた時、
試してみるをたのしみに思う。 20 クラスメイトの間では私はいつも新しい革新
的なテクノロジーを一番最初に試している。 21 モバイル機器をインフォーマル英語学習に使
ってみるつもりである。 22 23 モバイル機器を頻繁にインフォーマル英語学
習で使うだろうと思う。 将来、インフォーマル英語学習のためにモバ
イル機器の使用を増やすつもりである。 24 インフォーマル英語学習のためにモバイル機
器を楽しんで使うと思う。 25 モバイル機器をインフォーマル英語学習で使
うことを他の人に薦めたいと思う。 26 使用法 164
下記の質問をよく読み、あなたの意見に該当する欄１つにチェックまたは回答を記入し
てください。 モバイル機器をインフォーマル英語学習に使う時は、どれぐらいの頻度で使いますか？ まったく
な い ま れ に あ る と き ど き 頻 繁 に い つ も 27 英語のウェブサイト 28 英語のソーシャルネットワーキ
ングサイト 29 英語の学習アプリケーション 30 英語のゲーム 31 英語の音楽 32 33 英語の音声 (例:ポッドキャスト ) 英語の動画 （例:YouTube) 34 英語のドラマ、映画 35 辞書アプリケーション 36 翻訳アプリケーション 37 英語の電子書籍 38 英語のニュース 39 その他 (回答を記入をしてください) 165
40. インフォーマル英語学習に使用している機器で該当するものすべてにチェック(✔︎)してく
ださい。 a. ____ 携帯電話またはスマートフォン b. ____ MP3 プレーヤー (例：iPod Nano、 ウォークマン) c. ____ 電子書籍リーダー(例：Kindle、Kobo) d. ____ タブレット (例：iPad、Galaxy Tab) e. ____ 携帯型ゲーム機 (例：ニンテンドーDS、PSP) f. ____ その他 (記入をしてください) __________________________ 41. インフォーマル英語学習のためにモバイル機器を週に平均どれくらい使いますか。 ________ 時間 42. インフォーマル英語学習にモバイル機器を使う時は、主に … (複数回答不可) a. ____ 学習のために使っている b. ____ 学習に関わるとは気づかずに使っている 情 報 下記の質問にお答えください。 43. あなたの年齢は？ ________ 歳 44. あなたの国籍は？ ________________________________________ 下記の質問は該当する項目１つだけにチェック(✔︎)をしてください。 45. あなたの性別は? a.___ 男性 b.___ 女性 c.___ 答えたくない 46. あなたの専攻は? a.___ 経済 b.___ 国際経済 166
c.___ 情報理工 d.___ その他（記入をしてください）__________________________ 47. あなたの学年は? a.___ １回生 b.___ ２回生 c.___ ３回生 d.___ ４回生 e.___ その他（記入してください） ___________________________________ 48. 所有しているモバイル機器すべてにチェック(✔︎)してください。 a. ____ 携帯電話またはスマートフォン b. ____ MP3 プレーヤー (例：iPod Nano、 ウォークマン) c. ____ 電子書籍リーダー(例：Kindle、Kobo) d. ____ タブレット (例：iPad、Galaxy Tab) e. ____ 携帯型ゲーム機 (例：ニンテンドーDS、PSP) f. ____ その他 (記入をしてください) __________________________ 自 由 記 入 式 質 問 下記の質問についてあなたの回答をご記入ください。 49.インフォーマル英語学習にモバイル機器を使うことの長所は何だと思いますか。 _____________________________________________________________________________________
_____________________________________________________________________________________
______________________________________________ 50.インフォーマル英語学習にモバイル機器を使うことの短所は何だと思いますか。 _____________________________________________________________________________________
_____________________________________________________________________________________
______________________________________________ アンケートにお答えいただきありがとうございます！研究へのご協力感謝いたします。 167
168
Appendix D: Cover Letter (Japanese)
学生のみなさんへ
私達はスマートフォンやタブレットなどのモバイル機器がインフォーマル英語学習にどのよう
に使われ、受け入れられているかを研究しています。ぜひとも皆さんにこのアンケートに参加
していただきたいと思います。時間は10分ほどしかかかりません。この研究は私個人で行うも
のでXXX大学や言語教育センターとは関わりはありません。
アンケートに答えていただける場合は下記の言葉の定義を念頭に入れてくだ
モバイル機器とは
モバイル機器とはスマートフォン、タブレット、MP3プレーヤーのような携帯することができ、
手に持って操作ができる電子機器で、言語教育に利用可能なものです。
インフォーマル英語学習とは
インフォーマル（非公式）英語学習とは、構造化された授業、例えば大学の英語の授業や英会
話スクールのレッスンなどに直接関わりのない学習で、英語の上達につながる可能性がある活
動 全てを意味します 。
インフォーマル英語学習は意識的に、また無意識に行われます。
（例え）意識的とは・・・英語の映画を英語の勉強のために観ること
無意識的とは・・英語の映画を娯楽のために観ること
このアンケートに答えることは任意です。全ての質問は無記名でありリスクは最低限です。も
しアンケートに答えられない場合や途中で参加をやめた場合は、アンケート用紙の返却は不要
です。アンケートに参加されなくてもペナルティや不利益は発生しませんし、成績評価には一
切関わりはありません。アンケートは授業時間外に記入いただき、次の授業で担当教員にお渡
しください。また、アンケート用紙に名前は書かないでください。アンケートの提出をもちま
して、上記の事項ついて同意いただいたと理解させていただきます。
何か質問がある場合、またこの研究の結果がほしい場合は、下記までご連絡ください。
• ダニエル ミルズ XXX 大学 [[email protected]]
•
ドリス
ボリガー
ワイオミング大学 [[email protected]]
この研究はワイオミング大学のIRB（倫理審査委員）から承認を得ています。もし研究
の参加者としてのあなたの権利について質問がある場合は、ワイオミング大学IRBオフ
ィス1-(307) 766-5320までお問い合わせください
研究へのご協力に感謝します。ありがとうございます！
169
Appendix E: Cover Letter (English)
Dear Student,
We are conducting research on the use and acceptance of mobile devices, such as smartphones
and tablets, for informal English-language learning. We would like to invite you to complete a
questionnaire that will take approximately 10 minutes of your time. This is a private research
study and is not connected to XXXX University or the Language Education Center.
When filling out the survey please keep in mind the following definitions:
Mobile devices are smartphones, tablet computers, MP3 players and other portable, hand-held,
electronic devices that can be used for the learning of languages.
Informal English-language learning is any activity that has the potential to improve your
proficiency in English but is not directly related to structured classes like the ones you take at
university or at a private language school. Informal English-language learning can occur
consciously (i.e., watching an English-language movie for the purpose of study) or
unconsciously (i.e., watching an English-language movie for entertainment).
Participation is voluntary, all responses are anonymous, and minimal risk is involved. If you
wish to withdraw or not complete the questionnaire, please do not return the survey. Refusal to
participate will involve no penalty or loss of benefits to which you may be entitled and does not
effect your grade in any way. Please complete the survey outside of class and return it to your
instructor next week. Do not write your name on the survey. When you return the survey, you
explicitly express your informed consent to participate in the study.
If you have any questions or would like a copy of the results, please contact any of us:
•
•
Daniel Mills, XXXX University [[email protected]]
Doris Bolliger, University of Wyoming [[email protected]]
This study has been approved by the Institutional Review Board (IRB) of the University
of Wyoming (UW). If you have any questions about your rights as a research subject,
please contact the IRB Office at UW at (307) 766-5320.
Thank you for assisting us with our research!
170
Appendix F: IRB Approval
Vice President for Research & Economic Development
1000 E. University Avenue, Department 3355 • Room 305/308, Old Main • Laramie, WY 82071
(307) 766-5353 • (307) 766-5320 • fax (307) 766-2608 • www.uwyo.edu/research
June 3, 2015
Daniel Mills
Graduate Student
Professional Studies
University of Wyoming
Faculty Advisor: Dr. Doris Bolliger
Protocol # 20150603DM00822
Re: IRB Proposal “The use and acceptance of mobile devices for the purpose of informal
English-language learning in the Japanese university context”
Dear Mr. Mills:
The proposal referenced above qualifies for exempt review and is approved as one that would not
involve more than minimal risk to participants. Our exempt review and approval will be reported to the
IRB at their next convened meeting June 18, 2015.
Any significant change(s) in the research/project protocol(s) from what was approved should be
submitted to the IRB (Protocol Update Form) for review and approval prior to initiating any change. Per
recent policy and compliance requirements, any investigator with an active research protocol may be
contacted by the recently convened Data Safety Monitoring Board (DSMB) for periodic review. The
DSMB’s charge (sections 7.3 and 7.4 of the IRB Policy and Procedures Manual) is to review active
human subject(s) projects to assure that the procedures, data management, and protection of human
participants follow approved protocols. Further information and the forms referenced above may be
accessed at the “Human Subjects” link on the Office of Research and Economic Development website:
http://www.uwyo.edu/research/human-subjects/index.html.
You may proceed with the project/research and we wish you luck in the endeavor. Please feel
free to call me if you have any questions.
Sincerely,
Colette Kuhfuss
Colette Kuhfuss
IRB Coordinator
On behalf of the Chairman,
Institutional Review Board
171