Relationships Between Perceived Learning

JOURNAL OF TEACHING IN PHYSICAL EDUCATION, 1996.15.369-383
O 19% HUMAN KINETICS PUBLISHERS, INC.
Relationships Between
Perceived Learning Environment and
Intrinsic Motivation in Middle School Physical Education
Stephen A. Mitchell
Kent State University
In this article, a study focusing on the perceptions and motivations of middle
school students in physical education classes is described. The Physical Education Learning Environment Scale (PELES) was developed to measure student perceptions of learning environment, or class climate, in physical education on dimensions of perceived challenge, perceived threat to sense of self,
perceived competitiveness, and perceived control. The PELES was administered, together with the Intrinsic Motivation Inventory (IMI) to a sample (N =
622) of middle school students. Exploratory factor analyses provided evidence
of adequate construct validity for the PELES, following elimination of the
perceived control suhscale. Multiple regression analyses in'dicated that perceived threat and perceived challenge predicted intrinsic motivation for both
males and females. These findings are discussed in terms of their implications
for practicing teachers and for future research.
An area of concern for physical educators is the motivation of adolescents
to participate in physical activity. These concerns arise out of research suggesting that youth health and fitness levels have fallen below acceptable standards.
In the National Children and Youth Fitness Study, Ross and Gilbert (1985) found
that from a sample of 8,800 secondary school students, only 41% felt they regularly exerted themselves during exercise. Furthermore, only 59% engaged in appropriate physical activity on a year-round basis, and most juniors and seniors
did not take physical education as an elective. Motivation for involvement in
physical education is clearly a concern for educators. Though motivation has been
well studied in classroom and organized sport settings, there is a dearth of research relating to motivation for participation in school physical education (Lee,
1991; Silverman, 1991).
Motivation may come from numerous sources, but intrinsic motivation is particularly important in physical education and sport. Intrinsic motivation is the degree
to which an individual chooses to participate in an activity for the pleasure derived
rather than for any extrinsic reward that may be forthcoming (Deci & Ryan, 1985).
When people are intrinsically motivated, they experienceinterest in an activity, enjoyment, and feelings of competence and control. Voluntary participation in physical
Stephen A. Mitchell is with the School of Exercise, Leisure and Sport at Kent State
University, 264 Memorial Gym Annex, Kent, OH 44242.
MITCHELL
370
activity rests largely on intrinsic motivation because extrinsic rewards are rarely
available to those other than elite performers. In addition, motivation researchers suggest that extrinsic rewards may not be effective in encouraging continued physical activity (for a review of this literature, see Ryan, Vallerand, &
Deci, 1984).
Perceptions and Motivation in Physical Education
Fox (199 1) examined two perspectives on motivation for activity with specific reference to physical education in schools. One perspective suggests that providing opportunities for physical activity in childhood will lead to the production
of continuing activity habits. However, Fox casts doubt on this "mechan~sticview"
by suggesting that it reduces the issue to one of teachers guaranteeing a certain
amount of regular activity. Such a view, he suggested, implies that children have
no voice in the decision-making process and that various circumstances related to
the activity, such as its context and meaning, are seen as less relevant. Furthermore, given the importance of choice in Deci and Ryan's (1985) conceptualization
of intrinsic motivation, this mechanistic perspective does not seem able to account
for differences in motivation to engage in physical education.
Fox (1991) proposed an alternative perspective, which he terms a "cognitive-developmental" perspective. From this viewpoint, educators would base curricular and teaching decisions upon students' increasingly sophisticated perceptions and decision-making capacities regarding involvement in physical activity.
Hence, children's interpretations of physical activities and experiences become
crucial in determining future voluntary participation. The activity itself would take
on a more neutral role, with the perceptions formulated about physical activity
providing the key to future motivation and participation. For example, perceptions
of optimal challenge, personal control, and self-competence are particularly important for enhancing intrinsic motivation (Deci & Ryan, 1985).
The cognitive-developmental perspective proposed by Fox (1991) has theoretical grounding in the classroom research of Eccles and her colleagues (Eccles [Parsons] et al., 1983). This work has sought to explain motivation through an expectancy-value model based on the assumption that an individual's interpretation of reality, rather than reality itself, directly influenceschoice to engage in an activity (Eccles
& Harold, 1991). Simply put, if an individual perceives a positive or successful experience, he or she will more likely choose to participate with intensity and to persist in
that activity. The relationship between student perceptions and motivation has been
documented in the classroom by studies to test the expectancy-value model. At the
middle school level, declines in motivation and performance have been associated
with changing school and classroom environments (Eccles, Wigfield, Midgley, et al.,
1993; Wigfield, Eccles, Mac Iver, Reuman, & Midgley, 1991).
The construct of student perception has been conceptualized and investigated in other ways. One line of research has pursued the investigation of
perceived motivational climate in the classroom and in interscholastic sport.
Findings suggest that the perception of a mastery-focused environment, in
which students perceive an emphasis on task mastery rather than on demonstrating high ability, facilitates the development and maintenance of adaptive
motivational patterns (Ames &Archer, 1988; Seifriz, Duda, & Chi, 1992). A
ENVIRONMENTAND MOTIVATION
371
further conceptualization of student perception, namely perceived learning
environment, has received considerable attention in classroom research and is
central to the purpose of this study.
The effect of student perceptions of learning environments has been examined
thoroughly in classroom research (for a review of this literature see Walberg, 1976).
Walberg (1976) proposed a perceptual model which holds that "the student's conscious perception of internal and external stimuli and his choices are the proximate,
mediating determinants of learning" (p. 142).Walberg cited findings that reveal consistent effects of perceived learning environment,on both motivation and performance,
across different classroom subjects. Research on perceived learning environment in
physical education has, however, been limited to that of Ward (1982), who investigated students' perceptions of the learning environment in secondary school physical
education. Ward concluded that perceptions of learning environments in physical education varied and were related to student and teacher gender.
Gender differences in perceptions and motivation have been well documented.
In addition to Ward's (1982) findings, researchers have demonstrated that males
and females at both elementary and middle school levels differ in their perceptions
of the importance, usefulness, and enjoyment of subjects such as mathematics,
English, music, reading, and sport (Eccles &Harold, 1991;Eccles, Wigfield, Harold,
& Blumenfeld, 1993). These perceptions have implications for motivation, and
knowledge of such gender differences is critical for teachers who must seek to
establish learning environments that will enhance motivation in all students.
The present study sought to further investigate the construct of perceived
learning environment in physical education. Given the extent and results of classroom research on perceived learning environment, it is perhaps surprising that
investigation of this construct has not been conducted more extensively in physical
education. Specifically, this study had three purposes:
1. To develop instrumentation to measure perceived learning environment in
physical education
2. To investigate gender differences in intrinsic motivation and selected
dimensions of perceived learning environment
3. To determine the extent to which student perceptions of learning environment predict intrinsic motivation for participation in physical education
Although it is possible to investigate numerous dimensions of the perceived learning environment, this study was limited to student perceptions of challenge, competitiveness, internal control over outcomes, and threat to self-esteem. These dimensions were selected for their probable impact on intrinsic motivation, as suggested in relevant literature (Csikszentmihalyi, 1975;Deci, Betley, Kahle, Abrarns,
& Porac, 1981; Deci & Ryan, 1985; Ryan et al., 1984).
Method
Participants
Participants for the study were drawn from two middle schools in a suburban school district and were split in terms of gender and grade level. Intact classes
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MITCHELL
from three grade levels (Grades 6-8, age 11-14) were selected on the basis of
availability and the need for minimum disruption of the schools' schedules.
Instrumentation a n d Procedures
Perceived Learning Environment. Questionnaire items were developed to
measure perceived learning environment using a 5-point Likert scale (1 = strongly
agree to 5 = strongly disagree). This instrument, the Physical Education Learning
Environment Scale (PELES), contained a total of 24 items. Six items measuring
perceived challenge and 4 measuring perceived competitiveness were generated
by rewording items from the perceived difficulty and perceived competitiveness
subscales of the Learning Environment Inventory (Fraser, Anderson, & Walberg,
1983). Four items measuring perceived threat were developed in consultation with
a panel of experts. Ten items measuring perceived control were reworded from
those used by Ames and Archer (1988) with middle and high school students.
These perceived control items were worded to reflect causal factors suggested by
attribution theory (Weiner, 1974).Items referring to attributions to external factors
were rescaled prior to analysis so that disagreement indicated high perceived control. Five of these items reflected perceived internal control over favorable outcomes, and 5 reflected perceived control over unfavorable outcomes. All negatively stated items in the instrument were rescaled prior to data analysis. This original
version of the PELES is presented in the Appendix.
Intrinsic Motivation. To measure intrinsic motivation, students responded to
a version of the Intrinsic Motivation Inventory (IMI; Ryan, 1982) reworded for use in
sport settings by McAuley, Duncan, and Tammen (1989). This inventory assesses
levels of intrinsic motivation as an additive function of underlying dimensionslabeled
"interest-enjoyment," "perceived competence," "effort-importance," and "pressuretension." Each item in this case was worded to reflect students' general levels of intrinsic motivation without reference to any one particular lesson or activity. McAuley
et al. (1989) confirmed the factor structure of the MI by conducting both first- and
second-order factor analyses to generate a five-factor hierarchical model. The firstorder analysis indicated a simple structure in that each item only loaded significantly
on its anticipated factor. When the four factors were themselves analyzed in the second-order factor analysis, a single factor representing intrinsic motivation emerged
with all subscales loading significantly. Alternative Gersions of the IMI have been
adapted for use in sport settings,demonstratingthe flexibilityof this measure (McAuley,
Wraith, & Duncan, 1991; Whitehead & Corbin, 1991).
Together, the instruments comprised a total of 40 items, sufficient to measure
the variables under investigation, yetbrief enough to ensure swift completion and no
substantial loss of time from classes. The instruments were administered to a sample
(N= 622) of middle school students that was then randomly divided into two groups.
Data for the first group (n = 300) were used to analyze items and assess validity and
reliability of the instruments. The instruments were cross-validatedby using data for
the second group (n = 322) to measure the relationships under investigation.
Data Analysis
Factor analytic procedures were used for item reduction and to construct the
subscales of the PELES. This led to some reconfiguring of the instrument, includ-
ENVIROh'MENT AND MOTIVATION
373
ing the elimination of one subscale from the study. Reliability for the PELES
and IMI was established by computing Cronbach alpha reliability coefficients.
Following subscale revisions, Multivariate analysis of variance (MANOVA)
was used to investigate gender differences on all variables. A significant gender effect was further examined by univariate analyses of variance (ANOVA).
Pearson product-moment correlations and multiple regression analyses were
used to investigate relationships between variables. In the regression analyses, intrinsic motivation was the dependent variable and dimensions of perceived learning environment were the independent variables, entered into the
regression equation according to their degree of relationship with intrinsic
motivation (forward selection).
Results
Validity and Reliability of the Instruments
Physical Education Learning Environment Scale. Exploratory factor analyses were conducted to establish construct validity of the PELES. A principal components factor analysis yielded a four-factor model accounting for 47% of the
variance. Since relationships between dimensions existed, an oblique rotation was
conducted, retaining four factors. Factor loadings indicated that items developed
to measure perceived challenge, competitiveness, and threat loaded, for the most
part, on different factors. However, the picture was clouded by items designed to
measure perceived internal control. These items loaded significantly across all four
factors, and several had high negative loadings. In order to clarify the validity of
the first three factors, the internal control subscale was eliminated from the study
at this point, and a further exploratory factor analysis was conducted. This yielded
a three-factor solution accounting for 53% of the variance, with only these three
factors having eigenvalues of greater than one. Loadings were rotated (oblique) to
simple structure, with each item loading at greater than .40 on only one factor.
Loadings are reported in Table 1.
As can be seen, only two items loaded on unexpected factors. Item 3 ("In phys.
ed. classes we compete against each other") loaded on the same factor as five items
designed to measure perceived challenge.This is not unreasonable given that for some
students,a competitiveenvironmentwould be challenging in itself. Item 12 ("In phys.
ed. class I can do what the teacher wants easily") was expected to measure perceived
challenge and was reverse scored such that disagreement indicated a high perception
of challenge. However, this item loaded very heavily on the same factor as all four
items intended to measure perceived threat. Again, in retrospect, this may not be surprising, as it is easy to see how perceiving oneself unable to "do what the teacher
wants" would be very threatening for many students. Since all of these items had
factor loadings greater than .40, they were summed to form measures of perceived
challenge (Items 2,3,8, 16,22,24), perceived competitiveness(Items 7,13, 18), and
perceived threat (Items 5, 10, 12, 15,20). Cronbach alpha reliability coefficients for
these three subscales were .7 1, .71, and .75, respectively. Interfactor correlations were
low to moderate, ranging from -.07 to -.32.
Intrinsic Motivation Inventory. Although the IMI is composed of four
subscales, these were not of concern in this study as only a total measure of intrin-
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Table I Factor Loadings for the Three-Factor Model of Perceived Learning
Environment
Dimension
Item
Challenge
2
8
12
16
22
24
3
7
13
18
5
10
15
20
Factor 1
Factor 2
.73*
.02
.65*
-.05
.13
.81*
.72*
-.02
.O 1
.73*
.43*
.I1
Competitiveness
.51*
-.02
-.02
.15
-.06
-.03
.12
.OO
Threat
-.I7
.64*
-.39
.46*
.15
33"
-.I5
.59*
% variance accounted for
26
16
Cumulative % variance
26
42
* Factor loadings of >.40 were considered sufficient for item retention
.
Factor 3
-.lo
.17
-.35
-.01
.04
-.33
.27
.72*
.79*
.78*
.14
.05
.I1
.17
11
53
sic motivation was needed. Reliability for the full 16 items was found to be satisfactory with an alpha level of 34, though this could be increased to .88 by excluding Item 14 ("I am anxious during phys. ed. classes"). This item correlated negatively with the remaining 15 items and, it seems, was misinterpreted by many
subjects. Several students questioned whether the term "anxious" referred to being
"uptight" or "impatient to get started." Since it is possible that the latter represents
a view of anxious more commonly held by children, it may be wise to consider
rewording this item in future studies with children. As a result of these analyses,
Items 1-13 and Items 15-16 were summed to yield a composite measure of intrinsic motivation. Item 14 was eliminated at this point.
Having established validity and reliability of the instrumentation with part
(n = 300) of the total sample, the appropriate items were summed to form variables
for the 322 children randomly assigned to the second group, the data for which
was used to investigate relationships between variables.
Gender Differences
It was appropriate at this point to investigate possible gender differences in
intrinsic motivation and perceived learning environment, since failure to do so
could cloud interpretation of the relationships under investigation. If significant
gender differences in intrinsic motivation and perceived learning environment were
found, it would be necessary to conduct subsequent multiple regression analyses
ENVIRONMENTAND MOTIVATION
375
Table 2 Gender Differences for Dimensions for Perceived Learning Environment
Boys
Variable
Intrinsic motivation
Perceived challenge
Perceived threat
Perceived competitiveness
Girls
M
SD
62.46
24.36
9.77
8.32
7.18
3.46
3.29
3.21
M
SD
57.00 8.94**
22.11 3.45**
11.67 3.53*
7.15
2.47*
by gender, because different patterns of relationships might exist for males and
females. This is particularly important to the study because the investigation of
gender differences in perceptions can provide both practitioners and researchers
with insights into the different ways male and female students view the learning
environment.
MANOVA was employed to test gender differences for all variables. This
analysis revealed a significant overall gender effect, Wilks's lambda = 3 0 , F(4,
278) = 17.80, p < .000 1. Subsequent ANOVA for each variable indicated significant gender differences for intrinsic motivation, F(1, 281) = 32.13, p < .0001;
perceived threat, F(1, 28 1) = 34.4 1, p < .000 1; perceived challenge, F(1, 28 1) =
3 1.40, p < .0001; and perceived competitiveness, F(1, 28 1) = 9.56, p < .01. Descriptive statistics, reported in Table 2, indicated that boys scored significantly
higher on intrinsic motivation, perceived challenge, and perceived competitiveness, but lower on perceived threat.
Intrinsic Motivation and Perceived Learning Environment
Correlational Analyses. To determine the relationships between intrinsic
motivation and the three dimensions of perceived learning environment, each dimension was plotted against intrinsic motivation and Pearson product-moment correlation coefficients were computed for boys and girls. No curvilinear relationships were
apparent from the plots. Results of the correlational analyses are given in Table 3.
Also shown are intercorrelations between dimensions of learning environment.
The data in Table 3 indicate that for both boys and girls, intrinsic motivation
correlated positively with perceived challenge and negatively with perceived threat.
The data also indicate that for boys, perceived competitiveness was negatively
related to intrinsic motivation.
Regression Analyses. Multiple regression procedures were used to determine whether perceived learning environment might predict intrinsic motivation.
Dimensions of learning environment were entered into the regression equation
according to their degree of relationship with intrinsic motivation. A significant
relationship was found between the three dimensions of perceived learning environment and intrinsic motivation for both boys, F(3, 138) = 58.71, p < .0001, and
girls, F(3, 137) = 67.31, p < .0001. Table 4 presents increments of R2 for each
dimension of perceived learning environment.
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Table 3 Correlations (Pearson r) Between Intrinsic Motivation and Perceived
Learning
Intrinsic
motivation
Perceived
challenge
Percieved
threat
Boys (n = 166)
Perceived challenge.
Perceived threat
Perceived competitive
.506**
-.707**
-.221*
-.388**
-.312**
.236*
Girls (n = 156)
Perceived challenge
Perceived threat
Perceived competitive
.540**
-.719**
-. 142
-.351**
-.09 1
.I44
Table 4 Increments of R2 for Multiple Regression of Intrinsic Motivation on
Dimensions of Percieved Learning Environment
Order of entry
Perceived threat
Perceived challenge
Perceived competitiveness
Incremental RZ(boys)
Incremental RZ(girls)
.49*
.07*
.00
R2= .56
For boys, the three predictor variables accounted for 56% of the variance in
the measure of intrinsic motivation. Perceived threat accounted for most of the
variance (49%), with perceived challenge accounting for only an additional 7%.
As might be expected, perceived challenge added little to the multiple correlation
and, as a result, to the variance explained by the regression equation. This is due to
high correlations between the dimensions of perceived learning environment, as
indicated in Table 3. Thus, a considerable amount of the variance in intrinsic motivation that could be explained by perceived challenge had already been accounted
for by perceived threat.
Nevertheless, results indicate that perceived threat was a negative predictor
of intrinsic motivation, suggesting that if a boy's perception of threat to sense of
self is low, then he is likely to be high in intrinsic motivation. Furthermore, despite
overlap between predictors, perceived challenge was also a significant predictor of
intrinsic motivation. Perceived competitiveness was not a significant predictor of
intrinsic motivation.
ENVIRONMENTAND MOTIVATION
377
For the girls, the three dimensions of learning environment predicted a greater
proportion of the variance in intrinsic motivation (60%). Once again, most of this
was explained by perceived threat (5 1%). Perceived challenge accounted for an
additional 9% of variance, and, as with the boys, there was no relationship between perceived competitiveness and intrinsic motivation.
Discussion
For intrinsic motivation to be enhanced, students must recognize the value
of participating in an activity for the sake of participation. The results of this study
suggest that perceived learning environment is a valid predictor of intrinsic motivation for middle school students. Results of the multiple regression analyses indicate that perceived threat and perceived challenge were the best predictors of intrinsic motivation in physical education for both boys and girls. Furthermore the
data suggest that intrinsic motivation is likely to be high when students perceive a
learning environmentto be nonthreatening to their self esteem and physically challenging. These findings are consistent with the intrinsic motivation literature (Deci
& Ryan, 1985). The key question now becomes, Under what circumstances are
students most likely to perceive challenge, but not threat? The answer to this question has implications for effective teaching practice.
Implications for Teaching Practice in Physical Education
Given that low perceived threat was the primary predictor of intrinsic motivation in this study, one possible avenue to enhance intrinsic motivation is to ensure that students view their abilities in physical education positively. This is consistent with literature suggesting a positive relationship between perceived ability
and motivation (for reviews of this literature see Feltz, 1988; Weiss, 1987). Perceived ability may be enhanced by providing experiences where students succeed.
For most students, repeated success should lead to a more positive feeling of selfworth and a lower perception of threat. The results of this study indicate that lower
perceived threat is associated with higher intrinsic motivation for both males and
females at the middle school level.
Continued success may only influence motivation in the short term. As tasks
become progressively more difficult, failure may occur at some point, unless the
teacher chooses to avoid setting tasks that will challenge students' abilities. Easy
tasks are not recommended, however, because perceived challenge was also found
to be a significant predictor of intrinsic motivation in this study. Furthermore, students might attribute success on easy tasks to the simplicity of the task rather than
to their own ability. The importance of setting tasks that are challenging is emphasized by the work of Csikszentmihalyi (1975, 1993), who suggests that an individual will experience flow states and greater enjoyment when the demands of a
task optimally challenge that individual's own perceived ability. On the other hand,
if teachers set tasks that are too easy or too difficult, students may experience
either boredom or anxiety.
Goal setting, the efficacy of which is supported by an abundance of literature (for a review of this literature, see Weinberg, 1992), may be an effective strategy by which teachers can ensure optimal challenge and enhanced motivation.
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MITCHELL
Whether participating in an individual or group activity, the setting of realistic but
challenging goals can ensure that students are faced with tasks appropriate to their
levels of ability. Personal goals for fitness programs, targets for improvement in
golf or archery scores, fewer unforced errors in a tennis match, or improved support play by a soccer team are all examples of how challenge can be facilitated
through mastery-focused goals. Teachers should perhaps be aware that goal-setting strategies might be particularly applicable for female students if they are to
feel challenged and not threatened in physical education lessons. Though the gender differences identified in Table 2 clearly need further investigation, girls in this
sample did score significantly lower on intrinsic motivation and perceived challenge, and higher on perceived threat than did boys.
Lastly, the relationship of perceived competitiveness to the other variables is
interesting (see Table 3). For both boys and girls, although not significantly for the
girls, perceived competitiveness was negatively related to both intrinsic motivation and perceived challenge, and was positively related to perceived threat. This
suggests that students who perceive a competitive learning environment are more
likely to perceive threat to their sense of self and are less likely to perceive challenge or be intrinsically motivated. Again, this finding is consistent with previous
research (Deci et al., 1981) and should be considered by teachers who might create
environments that are overtly competitive, forcing children to evaluate themselves
in relation to others.
To summarize, the results of this study suggest that teachers should adopt
strategies that encourage students to focus on goals related to task mastery while
also providing challenging experiences. Such strategies may lead students to perceive learning environments as nonthreatening and challenging. Furthermore, students holding these perceptions of environment are likely to exhibit higher levels
of intrinsic motivation.
Implications for Future Research
This study has several implications for future research. First, valid and reliable instrumentation has been developed for measuring perceived learning environment. Although this has been accomplished previously in classroom settings, it
has not been done in the context of physical education. The subscales for perceptions of challenge, threat, and competitiveness all showed evidence of construct
validity, though the dimension of perceived control was problematic and was eliminated from the study. Additional trials are obviously necessary to further develop
items to measure perceived control. It would also be of value to measure additional
dimensions of perceived learning environment by introducing new subscales to
the PELES. The addition of dimensions such as perceived choice, cohesiveness,
organizational structure, friction, and diversity would enable researchers to undertake more thorough investigations of the perceptions that students hold regarding
the learning environment in physical education.
Second, the study investigated relationships using motivation as a dependent
variable, thereby recognizing the importance of outcomes in the cognitive and
affective domains. Previous research has investigated psychomotor outcomes to a
greater extent than outcomes in other domains. Yet for many practicing physical
educators, the problem of motivating students is very real. Afocus on the outcome
ENVIRONMENTAND MOTIVATION
379
of student motivation can add to the body of knowledge concerning teaching and
learning in physical education. Also of interest are the apparent gender differences
in all variables measured in the study. These findings are consistent with those in
classroom research (EccIes & Harold, 1991; Eccles, Wigfield, Harold, et al., 1993),
and the question that now arises is, Why do such differences exist? In order to
explain gender differences, it would be necessary to conduct research of a more
qualitative nature, using interview techniques to probe more deeply into the feelings and perceptions of students. This would be valuable for its capacity to provide
practitioners with guidelines for working more effectively with both male and female students.
It would also be of interest for researchers to examine relationships between
perceived learning environment and outcomes in other domains. For example, studies investigating multivariate outcomes could look at perceptions of the learning
environment in relation to motivation, knowledge attainment, and motor-skill acquisition. To incorporate such a variety of outcomes into a research study using a
single sample could be advantageous. Most certainly, it would provide both researchers and practitioners with a more complete picture of teaching and learning
than can be achieved by conducting numerous single outcome studies with different samples.
Finally, having investigated predictive relationships, it may now be appropriate to investigate potential causality with regard to the variables used in this
study. Although perception is an internal process that is not easily manipulated,
this may not be the case for variables that might cause students to perceive the
learning environment in particular ways. Such variables could include achievement goal orientation and perceived ability. Researchers (Ames, 1984; Hall, 1990)
have been effective in manipulating both achievement goal orientations and selfperceptions of ability in order to investigate the effects of these variables on selected outcomes. Such a procedure is readily adaptable to either laboratory or field
settings and would be a logical progression for this line of research.
Conclusion
Researchers should continue to investigate the role that students play in
mediating their own learning. This applies particularly to student cognition and
affect, because, as Silverman (1991) suggests, studies in these areas are not well
represented in the literature. Previous studies investigating student mediating processes have focused on relating time and student engagement measures to achievement. Whether these variables are actually mediating processes, or simply teacherimposed processes is a matter for debate. It seems reasonable to suggest that unless students are well motivated, neither engagement time nor appropriate practice
trials will occur. In these terms, motivation takes on the role of a mediating process. Moreover, the use of overt, observable behaviors such as task completion
rates and time utilization is limited in its capacity to go beneath the surface in
discovering how students may mediate learning. The limitations of this approach
are assessed accurately by Lee (1991), who states the following:
Amore thorough understanding of how learning occurs from teaching would
require defining more precisely the student variables that might affect the
MITCHELL
380
quality of student engagement. It would be necessary to extend the time
mediating approach to include the covert responses operating and the study
of motivational, affective and cognitive aspects of student thinking during
instruction. (p. 377)
This study represents a step along what will hopefully be a productive path.
References
Ames, C. (1984). Competitive, cooperative and individualistic goal structures:A cognitivemotivational analysis. In R. Ames & C. Ames (Eds.), Research on motivation in
education: Student motivation (Vol. 1, 177-208).New York: Academic Press.
Ames, C., &Archer, J. (1988). Achievement goals in the classroom: Students' learning strategies and motivation processes. Joumal of Educational Psychology, 80,260-267.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass.
Csikszentmihalyi,M. (1993, February). The pleasure principle. Chicago Magazine, pp. 7376, 113-116.
Deci, E.L., Betley, G., Kahle, J., Abrams, L., & Porac, J. (1981). When trying to win: Competition and intrinsic motivation. Personality and Social Psychology Bulletin, 7,79-83.
Deci, E.L., & Ryan, R.M. (1985). Intrinsic motivation and self-determination in human
behavior. New York: Plenum Press.
Eccles (Parsons), J., Adler, T.F., Futterman, R., Goff, S.B., Kaczala, C.M., Meece, J.L., &
Midgley, C. (1983). Expectations, values and academic behaviors. In J.T. Spence (Ed.),
Achievement and achievement motivation (pp. 75-146). San Francisco: Freeman.
Eccles, J.S., & Harold, R.D. (1991). Gender differences in sport involvement: Applying the
Eccles' expectancy-value model. Journal of Applied Sport Psychology, 3,7-35.
Eccles, J., Wigfield, A., Harold, R.D., & Blumenfeld, P. (1993). Age and gender differences
in children's self- and task perceptions during elementary school. Child Development, 64,830-847.
Eccles, J.S., Wigfield, A,, Midgley, C., Reuman, D., Mac Iver, D., & Feldaufer, H. (1993).
Negative effects of traditional middle schools on students' motivation. The Elementary School Journal, 93,553-574.
Feltz, D.L. (1988). Self-confidence and sports performance. Exercise and Sport Sciences
Reviews, 16,423-457.
Fox, K. (1991). Motivating children for physical activity: Towards a healthier future. Journal of Physical Education, Recreation and Dance, 62(6), 34-38.
Fraser, B.J., Anderson, G.J., & Walberg, H.J. (1983). Assessment of learning environments:
Manual for Learning Environment Inventory (LEI) and My Class Inventory (MCI)
(3rd version). Perth: Western Australian Institute of Technology.
Hall, H.K. (1990). A social cognitive approach to goal setting: The mediating effects of
achievement goals and perceived ability (Doctoral dissertation, University of Illinois, 1990). Dissertation Abstracts International, 51, 1156A.
Lee, A.M. (1991). Research on teaching in physical education: Questions and comments.
Research Quarterly for Exercise and Sport, 64,374-379.
McAuley, E., Duncan, T., & Tammen, V. (1989). Psychometric properties of the Intrinsic
Motivation Inventory in a competitive sport setting: A confirmatory factor analysis.
Research Quarterly for Exercise and Sport, 60,48-58.
McAuley, E., Wraith, S., & Duncan, T. (1991). Self-efficacy, perceptions of exercise, and
intrinsic motivation for exercise. Journal ofApplied Social Psychology, 21, 139-155.
Ross, J.G., & Gilbert, G. (1985). The national children and youth fitness study: A summary
of findings. Journal of Physical Education, Recreation and Dance, 56(1), 45-50.
ENVIRONMENTAND MOTIVATION
381
Ryan, R.M. (1982). Control and information in the intrapersonal sphere: An extension of
cognitive evaluation theory. Journal of Personality and Social Psychology, 43,450461.
Ryan, R.M., ValIerand, R.J., & Deci, E.L. (1984). Intrinsic motivation in sport: A cognitive
evaluation theory interpretation. In W. Straub & J. Williams (Eds.), Cognitive sport
psychology (pp. 231-242), Lansing, MI: Sport ScienceAssociates.
Seifriz, J.J., Duda, J.L., & Chi, L. (1992). The relationship of perceived motivational climate to intrinsic motivation and beliefs about success in basketball. Journal of Sport
& Exercise Psychology, 14,375-39 1 .
Silvennan, S. (1991). Research on teaching in physical education. Research Quarterlyfor
Exercise and Sport, 64,352-364.
Walberg, H.J. (1976). Psychology of learning environments: Behavioral, structural or perceptual? In L.S. Shulman (Ed.), Review of education (Vol. 4, pp. 142-178). Itasca,
IL: Peacock.
Ward, D.S. (1982). Student perception of the classroom learning environment in physical
education. Journal of Teaching in Physical Education, 2(1), 19-28.
Weinberg, R.S. (1992). Goal setting and motor performance: Areview and critique. In G.C.
Roberts (Ed.), Motivation in sport and exercise (pp. 177-197). Champaign, IL: Human Kinetics.
Weiner, B. (Ed.) (1974). Achievement motivation and attribution theory. Morristown, NJ:
General Learning Press.
Weiss, M.R. (1987). Self-esteem and achievement in children's sport and physical activity.
In D.R. Gould & M.R. Weiss (Eds.), Advances in pediatric sport sciences. Vol. 2:
Behavioral issues (pp. 87-119). Champaign, IL: Human Kinetics.
Whitehead, J.R., & Corbin, C.B. (1991). Youth fitness testing: The effect of percentilebased evaluative feedback on intrinsic motivation. Research Quarterly for Exercise
and Sport, 62,225-231.
Wigfield, A., Eccles, J.S., Mac Iver, D., Reuman, D.A., & Midgley, C. (1991). Transitions
during early adolescence: Changes in children's domain- specific self-perceptions
and general self-esteem across the transition to junior high school. Developmental
Psychology, 27,552-565.
Appendix:
Physical Education Learning Environment Scale (PELES)
Strongly
agree
A
A
1. When I do well in
Phys. ed., it is because I try hard.
2. Phys. ed. classes
A
make me work
hard.
3. In phys. ed.
A
classes we
compete against
each other.
Agree Neutral Disagree
B
C
D
B
C
D
Strongly
disagree
E
Dimension
E
IC
B
C
D
E
CH
B
C
D
E
CO
MITCHELL
4. When I do badly
in phys. ed., it is
just because the
teacher didn't do
a good job.
5. I feel useless in
phys. ed. classes.
6. When I do well in
phys. ed. class, it is
because I am good.
7. We try to see who
is best in phys. ed.
class.
8. In phys. ed. class
I am pushed to the
best of my ability.
9. When I do well in
phys. ed., it is because of good luck.
10. Phys. ed. makes
me feel good about
myself.
11. When I do badly
in phys. ed., it is
because I am not
good enough.
12. In phys. ed. class
I can do what the
teacher wants
easily.
13. Winning games
is important in
phys. ed.
14. When I do well in
phys. ed., it is just
because the teacher
helped me.
15. I get wonied that
I will look stupid
in phys. ed.
16. I feel that I work
hard in phys. ed.
17. When I do badly
in phys. ed., it is
because I didn't
try hard.
18. In phys. ed. we
try to do better
than others.
E
IC
ENVIRONMENTAND MOTIVATION
19. When I do badly
in phys. ed., it is
just because of
bad luck.
20. Phys. ed. makes
me feel bad about
myself.
21. When I do wet1
in phys. ed., it is
just because the
task is easy.
22 Phys. ed. classes
challenge my
ability.
23. When I do badly
in phys. ed., it is
because the task
is too difficult.
24. I do not need to
work hard in
phys. ed. class.
A
A
A
A
A
A
Note. CH =perceived challenge; TH = perceived threat; CO =perceived competitiveness;
IC = perceived internal control (eliminated due to cross-loadings in initial exploratory factor analyses).