Validity and reliability evaluation of the 2 x 2 perceived motivational climate questionnaire in physical activity settings.
Guan, Jianmin
In recent years, the dichotomous achievement goal model has been
developed to the 2x2 model. However, the models used for measuring
student perceived motivational climates to date have been exclusively
based on the traditional dichotomous climate framework. There is a need
to develop a new scale to reflect and assess four different perceived
motivational climates: mastery-approach, mastery-avoidance,
performance-approach, and performance-avoidance climate. The purpose of
this exploratory study was to examine the validity and reliability for
the 2 x 2 perceived motivational climate questionnaire in physical
activity settings (PMCQPAS). Confirmatory factor analysis and Cronbach
alpha coefficients were used to assess factorial validity and internal
consistency of the scores produced by the 2 x 2 PMCQPAS. The results
revealed that the 2 x 2 PMCQPAS was fit for the data and produced valid
and reliable scores used to assess four different perceived motivational
climates in university physical activity settings.
Over the past 30 years, achievement goal theory has been recognized
as an important theoretical approach to understanding student motivation
and behavior in physical activity settings. According to achievement
goal theory, achievement goals and perceived motivational climates are
two important constructs and influence the cognitions, emotions,
persistency, effort, and behaviors of individuals in physical activity
contexts.
Achievement goals are conceptualized as the purpose (Ames, 1992a;
Maehr, 1989) or cognitive-dynamic focus (Elliot, 1997) of
competence-relevant activity. To date, many achievement goal researchers
used a performance-mastery goal dichotomous model to examine individual
differences in goal orientation. This model proposes that individuals
with a mastery goal orientation focus on the personal goals of learning,
improvement, understanding of their progress, or mastery based on
self-referenced standards (Ames, 1992a, 1992b; Nicholls, 1989).
Conversely, individuals reporting a performance goal orientation focus
on illustrating superior ability compared to others, surpassing
normative-based standards, 05 achieving success with little effort
(Ames, 1984, 1992b).
Perceived motivational climates are defined as student perceptions
of achievement goals stressed by the teacher (Ames, 1992a, 1992b).
Consistent with the dichotomous achievement goal model, the dominant
theoretical framework guiding research on perceived motivation climate
in both classroom and physical activity settings is the dichotomous
perceived motivational climates: performance and mastery climates (Ames,
1992a,
1992b; Goudas & Biddle, 1994; Papaioannou, 1998; Treasure,
1997; Xiang & Lee, 2002). Perceptions of a performance climate are
negatively associated with students' intrinsic motivation and the
belief that ability leads to success. In contrast, perceptions of a
mastery climate are positively associated with their intrinsic
motivation and the belief that effort leads to success. Treasure (1997),
for example, investigated the influence of perceived motivational
climate on elementary school children's beliefs about the causes of
success, feelings of satisfaction and boredom, perceived ability, and
attitude toward physical education. Study results confirmed these ideas
as high performance/low mastery climate students reported negative
attitudes toward the class, belief that success is a result of ability,
and an overall feeling of boredom. In contrast, high mastery/moderate
performance climate students reported positive attitudes toward the
class, high perceived ability, a belief that success is caused by both
effort and ability, and overall feelings of satisfaction.
Achievement goal research in physical activity settings has
established a link between achievement goals and perceived motivational
climate (Cury, Fonseca, & Rufo, 2002; Ntoumanis & Biddle, 1998;
Treasure & Roberts, 1998; Xiang & Lee, 2002). Generally,
students with performance goals are likely to perceive a motivational
climate as performance climate, while students with mastery goals tend
to perceive a motivational climate as mastery climate. Cury, Fonseca,
and Rufo (2002), for example, examined the relationship between the
achievement goals and perceived motivational climate among French high
school students. They reported that the performance goals were
positively related to the performance climate, while the mastery goals
were positively associated with the mastery climate.
Because of the close relationship between the achievement goals and
perceived motivational climates, achievement goal theorists (e.g., Dweck
and Leggett, 1988; Nicholls, 1989; Ntoumanis & Biddle, 1998; Roberts
& Treasure, 1995) suggested that there is a need to examine the
joint influence of achievement goals and perceived motivational climates
on the cognitive, affective, and behavioral patterns of individuals in
both academic and physical activity settings. Xiang and Lee (2002), for
example, examined the relationship among achievement goals, perceived
motivational climate, and students' self-reported mastery
behaviors. Results revealed that achievement goals and perceived
motivational climate were related to students' self-reported
mastery behaviors.
In recent years, the achievement goal model has been developed from
the dichotomous model to 2 x 2 achievement goal model. The major reason
is that there is a mixed pattern of results in the dichotomous model
among researchers examining performance goals. Some researchers (e.g.,
Elliot & Harackiewicz, 1996; Harackiewicz & Elliot, 1993) found
that performance goals generated adaptive achievement behavior (e.g.,
striving to do better than others), whereas other researchers (e.g.,
Butler, 1992; Elliot & Church, 1997; Elliot & Dweck, 1988)
revealed that performance goals elicited negative or maladaptive
processes and outcomes.
In the 2 x 2 achievement goal model, four independent achievement
goals are supposed to account for competence-based strivings: (a)
mastery-approach goals that focus on mastering tasks, learning, and
understanding, (b) mastery-avoidance goals that try to avoid
misunderstanding, avoid not learning or not mastering a task, (c)
performance-approach goals that focus on the attainment of favorable
judgments of competence, and (d) performance-avoidance goals that try to
avoid unfavorable judgments of competence. Analyses of test validity and
internal consistency provide strong support for this model in both
academic settings (Elliot & McGregor, 2001) and physical activity
settings (Conroy, Elliot, & Hofer, 2003; Guan, Xiang, McBride, &
Brune, 2006). Additionally, achievement goal researchers have showed
that the 2 x 2 model provided a better fit to the data than dichotomous
models in both classroom (Elliot & McGregor, 2001) and physical
activity settings (Conroy, Elliot, & Hofer, 2003).
Compared with achievement goal model research, however, the
research on motivational climates and the questionnaires used for
measuring student perceived motivational climates to date are
exclusively based on the traditional dichotomous climate models.
Papaioannou (1994), for example, developed a 27-item Learning and
Performance Orientations in Physical Education Classes Questionnaire to
measure perceptions of learning (mastery) and performance orientations
in physical education classes. The results revealed that high intrinsic
interest and positive attitudes toward the school physical education
classes were related to the mastery-oriented climates, and unrelated to
the performance-oriented climates.
Another important instrument designed to measure the perceived
motivational climate in school settings is Seifriz, Duda, &
Chi's (1992) Perceived Motivational Climate in Sport Questionnaire
(PMCSQ). The PMCSQ aims to examine athletes' perceptions of the
motivational climate created by their coach. In recent years, PMCSQ has
been modified to measure students' perceptions of the motivational
climate during physical education classes. Dunn (2000), for example,
used the modified PMCSQ to examine the relationships among perceptions
of the motivational climate, goal orientations, and perceived competence
of children with movement difficulties in Grades 4 to 6. The results
from Dunn's (2000) study suggest that physical education classes
emphasizing a mastery motivational climate may lead to higher perceived
competence in children with movement difficulties.
With the appearance of the 2 x 2 achievement goal model, the
dichotomous climate framework may not reflect students' perceived
motivation climate accurately. There is a need to develop a new scale to
reflect and assess four different perceived motivational climates: (a)
Mastery-Approach Climate that assesses the degree to which students feel
that their teacher emphasized learning progress and understanding as
primary goals in physical activity settings; (b) Mastery-Avoidance
Climate that assesses the degree to which students feel that their
teacher emphasizes not performing worse than before or not losing their
skills and abilities, or striving to avoid making any mistakes or doing
anything wrong or incorrectly; (c) Performance-Approach Climate that
assesses how true it is that students feel that their teacher emphasizes
that outperforming other students and showing how smart they are in
physical activity settings are important goals; and (d)
Performance-Avoidance Climate that assesses how much students feel that
their teacher emphasizes the importance of avoiding appearing
incompetent and avoiding doing worse than others in class.
With this in mind, a newly devised 2x2 perceived motivational
climate questionnaire in physical activity settings (PMCQPAS) was
developed by the primary author. The questionnaire consists of 20 items,
which reflect four types of perceived motivational climate:
mastery-approach climates (e.g., "Is happy when we are improving
after showing some effort."), performance-approach climates (e.g.,
"Gives special treatment to those students who do best."),
performance-avoidance climates (e.g., "Tells us that it is
important that we don't look worse than others."), and
mastery-avoidance climates (e.g., "Points out that it is important
for us not to perform worse than before."). Each perceived
motivation climate includes five items. Content validity of 20 items was
evaluated by a panel of achievement goal experts. Items were modified
several times until there was 100% agreement among the panel. The format
for all items is a 7-point Likert-type scale, ranging from 1 (not at all
true of me) through 7 (very true of me). The stem for the items is
"In this class, my instructor...". The purpose of this
exploratory study was to examine the evidence for the factorial validity
and reliability of the scores produced by the 2 x 2 PMCQPAS.
Methods
Participants
A total of 452 undergraduates from a large university in the
southern region of the United States volunteered to participate in this
study. Participants completed the 2 x 2 PMCQPAS in quite gym conditions.
In order to determine if the validity parameter estimates were invariant
across different samples, the full sample was divided in two subsamples
based on their major areas. A total of 203 undergraduates with a major
of kinesiology (126 male, 76 female, one missing) served as participants
in subsample 1. Students consisted of freshman (2.5%), sophomore
(12.4%), junior (30.8%), and senior (53.7%) graders. The majority,
42.3%, were Caucasian, with 41.3% Hispanic American, 7.5%, African
American, 2.5% Asian-American, and 6.5% others.
Participants in subsample 2 were 249 undergraduates with a major of
non-kinesiology (141 male, 108 female) such as Biology, Business,
Communications, Criminal Justice, Information Systems, Nursing, English,
etc.. Students consisted of freshman (10.4%), sophomore (27.7%), junior
(30.8%), and senior (53.7%). The majority, 43.0%, were Hispanic
American, with 41.1% Caucasian, 6.6%, Asian American, 4.7%, African
American, and 4.7% others.
Procedures
After obtaining institutional approval and informed consent from
the participants, the 2 x 2 PMCQPAS was administered by the researchers
during regularly scheduled 31 physical activity classes. The 2x2 PMCQPAS
took students approximately 10 minutes to complete. To ensure the
independence of students' responses, the students were spread out
to avoid seeing one another's responses. Additionally, the
researcher carefully monitored students while they completed the
questionnaires and answered any questions as needed. In an attempt to
avoid students' tendency to give socially desirable responses, the
researchers encouraged the students to answer as truthfully as possible
and ensured them that their instructors would not have access to their
responses, and thus their grades would not be impacted in any way.
Data analysis
Confirmatory factor analysis (CFA) was performed to examine the
factorial validity of test scores produced by the 2 x 2 PMCQPAS.
Multiple fit indices including the comparative fit index (CFI), the
Tucker-Lewis Index (TLI), the goodness of fit index (GFI), the root mean
square error of approximation (RMSEA) were employed to assess the
adequacy of the measurement model. Of these, CFI, TLI, and GFI values
exceeding .90 are generally considered indicators of a good fitting
model (Hu & Bentler, 1995), while RMSEA values less than .05 are
indicative of close fit, and values between .05 and .08 as indicative of
marginal fit of the model (Browne & Gudeck, 1993). Data were
analyzed using AMOS 5.0, and the models were estimated using maximum
likelihood method.
Additionally, a multistep analysis of invariance (Bollen, 1989;
Byrne, 2001; Heck, 1998) was used to assess and determine whether the
same parameter estimates for the 2 x 2 PMCQPAS are found in both
subsamples. The order of the invariance routine used for the invariance
analyses in this study was based on Bollen's (1989) suggestions:
(a) establishing a baseline model for the two subsamples, (b)
constraining the factor loadings to equivalence across two subsamples,
(c) setting the uniqueness (error) to equivalence across two subsamples,
with the factor loadings still constrained, and (d) constraining the
factor variance and covariance to be invariant across two subsamples,
with the factor loadings and uniqueness still constrained.
Finally, Cronbach's alpha coefficients were calculated to
examine the internal consistency of test scores produced by the 2 x 2
PMCQPAS. Although reliability (internal consistency) is acceptable if a
Cronbach alpha value is greater than .70 (Cronbach, 1951; DeVellis,
1991; Kline, 1998; Nunnally & Bernstein, 1994), some statisticians
(e.g., Aron, Aron, & Coups, 2005; Kline, 1999) noted that when
dealing with psychological constructs, alpha values below .70 might be
expected realistically because of the diversity of the constructs being
measured.
Results
CFA revealed that the initial hypothesized 2x2 PMCQPAS model did
not represent an adequate fit to the subsample 1 data ([chi square] =
453.86, df = 164, CFI = .79, GFI = .81, TLI =.75, and RMSEA = .09).
Examination of the modification indices suggests that the fit of model
can be improved substantially by deleting several items from the four
factors. After deleting a total of eight items, the modified 12-item (3
items for each subscale) model was reestimated. The CFA results
indicated that the modified 2x2 PMCQPAS model was fit for the data ([chi
square] = 87.23, df= 48, CFI = .95, GFI = .93, TLI =.93, and RMSEA=
.06).
To confirm the factorial validity of modified 2x2 PMCQPAS model,
the multiple fit indices were examined with subsample 2 and full sample.
CFA analysis for the subsample 2 generated similar findings to those
revealed in subsample 1 for the modified model ([chi square] = 103.08,
df = 48, CFI = .93, GFI = .94, TLI = .90, and RMSEA= .07). However, the
results from the full sample yielded higher goodness-of-fit indexes
([chi square] = 108.04, df = 48, CFI = .96, GFI = .96, TLI = .94, and
RMSEA = .05), indicating that the fit of modified 2x2 PMCQPAS model can
be improved by increasing the sample size.
Results of the multistep invariance analysis indicated a small loss
in fit when shifting from the least stringent model (M() to the most
stringent model ([M.sub.4]). However, the chi-square difference test
among models (M, through [M.sub.4]) indicated that only the factor
loadings were invariant, demonstrating a metric invariance across the
two subsamples. The summary of fit indices and invariance analysis for
the modified 2x2 PMCQPAS across the two subsamples and full sample is
presented in Table 1 and Table 2. Additionally, each of the 12
standardized factor loadings for subsample 1 (.56 -.79), subsample 2
(.55 - .91), and full sample (.56 - .83) was statistically significant
(see Table 3), which further provides evidence that all the items are
strong indicators of the factors they are hypothesized to measure.
Finally, the results for reliability analyses were presented in
Table 4. Cronbach alpha coefficients for the Mastery-Approach Climates,
Performance-Approach Climates, Performance-Avoidance Climates, and
Mastery-Avoidance Climates exceeded.70 or were very close to .70 in
subsample 1, subsample 2, and full sample, indicating the internal
consistency of the score produced by the modified 2x2 PMCQPAS was
marginally acceptable. The means, standard deviations, and correlation
coefficients based on the modified 2x2 PMCQPAS were also presented in
Table 4. Only mastery-approach climates had an average score above the
midpoint of the scale. The standard deviations ranged from .71 to 1.39.
The correlation coefficients of the four factor scores ranged from .01
to .59. The relatively low correlations suggest that Mastery-Approach
Climates, Mastery-Avoidance Climates, Performance-Approach Climates, and
Performance-Avoidance Climates represent four independent constructs.
Discussion
The purpose of this study was conducted to investigate and examine
the reliability and validity for the 2 x 2 PMCQPAS. CFA, multistep
invariance analysis, and Cronbach alpha coefficients were used to assess
factorial validity and internal consistency of the scores produced by
the 2 x 2 PMCQPAS. The results confirm the appropriateness of using the
2 x 2 PMCQPAS in university physical activity settings. Scores from the
Mastery-Approach Climates, Mastery-Avoidance Climates,
Performance-Approach Climates, and Performance-Avoidance Climates
exhibited favorable psychometric properties of factorial validity. All
fit indices were in the acceptable range, which suggests that the 2 x 2
PMCQPAS produced valid scores as well as four distinct motivational
climates. However, the multistep invariance analysis revealed metric
invariance across the two subsamples with only factor loadings invariant
across the subsamples. A possible explanation for this finding might be
that the both subsample sizes was not large enough. For example, all fit
indices were improved when put two subsamples together. Follow-up study
is required to support or refute this supposition.
Although Cronbach's alpha coefficients for the
Mastery-Avoidance Climates, Performance-Approach Climates, and
Performance-Avoidance Climates factors did not reach .70, but they were
very close to it and thus should be considered marginally acceptable due
to the fact that the alpha value is very sensitive to the number of
items (McDonald,
1999) and fewer items tend to have a lower alpha value (Garson,
2007; McDonald, 1999). Given that there were only three items in each
subdomain, it is very possible that the low alpha was due to the small
number of items. Second, due to the diversity of the constructs being
measured, alpha values below .70 might be expected realistically when
dealing with psychological constructs (Kline, 1999). As Aron, Aron, and
Coups (2005, p. 283) noted that "In general, in the social and
behavioral sciences, a good measure should have a Cronbach's alpha
of at least .6 or .7 and preferably closer to .9". Therefore, it is
reasonable to suggest that the scores from the 2 x 2 PMCQPAS were
marginally reliable internal consistency in the university physical
activity settings.
A major goal of physical education is to motivate student
participation in physical activity on a regular basis. Understanding
students' perceived motivational climates can help physical
educators to motivate students to participate in physical activities
because different climates affect students' cognition, emotions,
behaviors, persistence and effort toward physical activities (Ntoumanis
&Biddle, 1998). As previously mentioned, however, research on
students' perceived motivational climate in physical activity
settings relies exclusively on the dichotomous climate model. Although
these research play an important role in assessing students'
perceived motivational climates, the dichotomous climates model may not
reflect the development of achievement goal theory and not able to
assess students' multi-faced perceived motivational climates. A
valid and reliable 2x2 PMCQPAS may make an important contribution to
achievement goal climates research because it offers a theoretically
sound means to assess students' perceived climate in physical
activity contexts.
The present study served as an exploratory analysis of the 2 x 2
PMCQPAS to the university physical activity settings. Based on the
current findings, we are confident that the 2x2 PMCQPAS can produce
valid and reliable scores when used to assess college students'
perceived motivational climates in physical activity settings. However,
it is important to note that validation is a continuous process, and
additional research is needed to continue to examine other forms of
validity and reliability of the 2 x 2 PCMQPAS with larger and more
diverse samples. For example, more multistep invariance analyses should
be expanded to different cultures, gender, and school levels to assess
the stability and generalizability of the 2 x 2 PMCQPAS. Such work will
facilitate application on the assessment of students' perceived
motivational climate and help physical educators develop students'
positive motivation toward physical education class. Additionally,
test-retest reliability should be examined to see if how consistent the
scores produced by the 2 x 2 PMCQPAS are over time. Future research
should also examine the predictive validity to see if the score produced
by the 2 x 2 PMCQPAS can predict outcome variables such as
students' effort and persistence toward physical activities.
Finally, all items in the 2 x 2 PMCQPAS are general to physical activity
contexts. Based on the 2 x 2 PMCQPAS, the future perceived motivational
climates questionnaire should include items specific to the physical
activities.
Jianmin Guan
University of Texas at San Antonio
Address correspondence to: Jianmin Guan, Dept, of Kinesiology,
Health, & Nutrition, University of Texas at San Antonio, One UTSA
Circle, San Antonio, TX 78249. Phone: (210) 458-5406, Fax: (210)
458-5873, E-mail: jguan@utsa.com
References
Ames, C. (1992a). Classrooms: goals, structures, and student
motivation. Journal of Educational Psychology, 84, 261-271.
Ames, C. (1992b). Achievement goals and classroom motivational
climate. In J. Meece & D. Schunk (Eds.), Students 'perceptions
in the classroom (pp. 327-348). Hillsdale, NJ: Erlbaum.
Aron, A., Aron, E.N., & Coups, E.J. (2005). Statistics for the
behavioral and social sciences: A brief course (3rd ed.). Upper Saddle
River, NJ: Pearson Prentice Hall.
Bollen, K. A. (1989). Structural equations with latent variables.
New York: John Wiley.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of
assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing
structure equation models (pp. 136-162). Newbury Park, CA: Sage.
Butler, R. (1992). What young people want to know when: Effects of
mastery and ability goals on interest in different kinds of social
comparisons. Journal of Personality and Social Psychology, 62, 934-943.
Byrne, B. M. (2001). Structural equation modeling with AMOS: Basic
concepts, applications, and programming. Mahwah, NJ: Lawrence Erlbaum.
Conroy, D. E., Elliot, A. J., & Hofer, S. M. (2003). A 2 x 2
achievement goals questionnaire for Sport: Evidence for factorial
invariance, temporal stability, and external validity. Sport Psychology,
25, 456-476.
Cronbach, L. (1951). Coefficient alpha and the internal structures
of tests. Psychometrika, 16, 297-334.
Cury, F., Fonseca, D., & Rufo, M. (2002). Perceptions of
competence, implicit theory of ability, perception of motivational
climate, and achievement goals; A test of the trichotomous
conceptualization of endorsement of achievement motivation in the
physical education setting. Perceptual & Motor Skills, 95 (1),
233-244.
DeVellis, R. F. (1991). Scale development: Theory and application.
Newbury Park, CA: Sage.
Dunn, J.C. (2000). Goal orientations, perceptions of the
motivational climate, and perceived competence of children with movement
difficulties. Adapted Physical Activity Quarterly, 17, 1-19.
Dweck, C. S., & Leggett, E. (1988). A social-cognitive approach
to motivation and personality. Psychological Review, 2, 256-273.
Elliot, A. J. (1997). Integrating the "classic" and
"contemporary" approaches to achievement motivation: A
hierarchical model of approach and avoidance achievement motivation. In
M. Maehr & P. Pintrich (Eds.), Advances in motivation and
achievement (Vol. 10, pp. 243-279). Greewich, CT: JAI Press.
Elliot, A. J., & Church, M. A. (1997). A hierarchical model of
approach and avoidance achievement motivation. Journal of Personality
and Social Psychology, 72, 218-232. Elliot, A. J., & Harackiewicz,
J. (1996). Approach and avoidance achievement goals and intrinsic
motivation: A mediational analysis. Journal of Personality and Social
Psychology, 70, 461-475.
Elliot, A. J., & McGregor, H. A. (2001). A 2 x 2 achievement
goal framework. Journal of Personality and Social Psychology, 80,
501-519.
Elliot, E. S., & Dweck, C. S. (1988). Goals: An approach to
motivation and achievement. Journal of Personality and Social
Psychology, 54, 5-12.
Garson, D. (2007). Structural equation modeling. Retrieved on
October 18, 2007 from
http://www2.chass.ncsu.edU/garson/pa765/structure.htm#amosboot
Goudas, M., & Biddle, S. (1994). Perceived motivational climate
and intrinsic motivation in school physical education classes. European
Journal of Psychology of Education, 9, 241250.
Guan, J., Xiang, P., McBride, R., & Bruene, A. (2006).
Achievement goals, social goals, and students' persistence and
effort in high school physical education. Journal of Teaching in
Physical Education. 25, 58-74.
Harackiewicz, J., & Elliot, A. J. (1993). Achievement goals and
intrinsic motivation. Journal of Personality and Social Psychology, 65,
904-915.
Heck, R. H. (1998). Factor analysis: Exploratory and confirmatory
approaches. In G. A., Marcolides (Ed.), Modern methods for business
research (pp. 177-215). Mahwah, NJ: Lawrence Erlbaum.
Hu, L., & Bentler, P. M. (1995). Evaluating model fit. In R. H.
Hoyle (Ed.), Structural equation modeling: Concepts, issues, and
applications (pp. 76-99). London: Sage.
Kline, P. (1999). The handbook of psychological testing (2nd ed.).
London: Routledge.
Kline, R. B. (1998). Principles and practice of structural equation
modeling. New York: Guilford Press.
Maehr, M. L. (1989). Thoughts about motivation. In C. Ames & R.
Ames (Eds.), Research on motivation in education (Vol. 3, pp. 299-315).
New York: Academic Press.
McDonald, R. P. (1999). Test theory': A unified treatment.
Mahwah, NJ: Lawrence Erlbaum.
Nicholls, J. G. (1989). The competitive ethos and democratic
education. Cambridge, MA: Harvard University Press.
Ntoumanis, N., & Biddle, S. (1998). The relationship between
goal profile groups and perceptions of motivational climates in sport.
Scandinavian Journal of Medicine & Science in Sports, 8, 120-124.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory
(3rd ed.). New York: McGraw Hill.
Papaioannou, A. (1994). Development of a questionnaire to measure
achievement orientations in physical education. Research Quarterly for
Exercise and Sport, 65, 11-20.
Papaioannou, A. (1998). Students' perceptions of the physical
education class environment for boys and girls and the perceived
motivational climate. Research Quarterly for Exercise and Sport, 69,
267-275.
Roberts, G. C. & Treasure, D. C. (1995). Achievement goals,
motivational climate, and achievement strategies and behaviors in sport.
International Journal of Sport Psychology, 26, 64-80.
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, 375-391.
Treasure, D. C. (1997). Perceptions of the motivational climate and
elementary school children's cognitive and affective response.
Journal of Sport Exercise Psychology, 19, 278-290.
Treasure, D. C., & Roberts, G. C. (1998). Relationship between
female adolescents' achievement goal orientations, perceptions of
the motivational climate, belief about success and sources of
satisfaction in basketball. International Journal of Sport Psychology,
29, 211-230.
Xiang, P., Lee, A (2002). Achievement goals, perceived motivational
climate and students' self reported mastery behaviors. Research
Quarterly for Exercise and Sport, 73, 58-65.
Table 1
Summaiy of Goodness-of-Fit Indices and Invariance Analysis for the
2 x 2 PMCQPAS
Multiple Indices
[chi
Model square] df TLI GFI CFI RMSEA
Confirmatory factor analysis
1. Subsample 1 (n = 203) 87.23 48 .93 .93 .95 .06
2. Subsample 2 (n = 248) 103.08 48 .90 .94 .93 .07
3. Full sample (N = 452) 108.04 48 .94 .96 .96 .05
Invariance analysis
1. Equal structure 190.31 96 .91 .93 .94 .05
2. Equal factor loadings 204.79 104 .91 .93 .93 .05
3. Equal uniquenesses 236.39 117 .91 .92 .92 .05
4. Equal variances and 361.08 126 .91 .91 .91 .05
covariances
Table 2.
Goodness-of-Fit Statistics for Chi Square Difference Tests
Model [DELTA][chi
Comparisons [X.sup.2] df square] [DELTA]df P
M1 190.31 96 -- -- --
M2-M1 204.79 104 14.48 8 >.05
M3-M2 236.39 117 31.60 13 <.01
M4-M3 361.08 126 124.69 9 <.001
Note. Ml = Equal structure; M2 = Equal factor loadmgs; M3 = Equal
uniquenesses; M4 = Equal variances and covariances.
Table 3
Standardized Factor Loadings for Subsample 1, Subsample 2, and Full
Sample
Subsample Subsample Full
1 2 Sample
Variables (n=203) (n=249) (n=452)
Mastery-approach climate 1 0.79 0.55 0.66
Mastery-approach climate 2 0.70 0.71 0.71
Mastery-approach climate 3 0.75 0.91 0.83
Mastery-avoidance climate 1 0.65 0.64 0.66
Mastery-avoidance climate 2 0.68 0.65 0.66
Mastery-avoidance climate 3 0.56 0.59 0.56
Performance-approach climate 1 0.64 0.57 0.62
Performance-approach climate 2 0.64 0.67 0.65
Performance-approach climate 3 0.73 0.65 0.68
Performance-avoidance climate 1 0.58 0.56 0.58
Performance-avoidance climate 2 0.63 0.66 0.67
Performance-avoidance climate 3 0.65 0.74 0.69
Table 4
Cronbach s Alpha Coefficients, Mean Scores, SD, and Correlations for
Four Subscales
Subsample 1 Subsample 2
(n = 203) (n = 249)
Subscale M SD Alpha M SD Alpha
l.MAPc 6.28 .81 .78 6.40 .71 .76
2.MAVc 3.16 1.27 .66 3.15 1.26 .66
3.PAPc 2.85 1.30 .71 2.54 1.23 .66
4.PAVc 3.29 1.26 .66 2.87 1.39 .70
Full sample
(N = 452) Correlation
Subscale M SD Alpha 1 2 3 4
l.MAPc 6.34 .76 .77 1.00
2.MAVc 3.44 1.36 .66 .01 1.00
3.PAPc 2.68 1.27 .69 -.19 ** 49 ** 1.00
4.PAVc 3.06 1.35 .69 -.11 * .52 ** .59 ** 1.00
Note. MAPc = Mastery-approach climate; MAVc = Mastery-avoidance
climate; PAPc = Performance-approach climate; PAVc = Performance-
avoidance climate. * p < .05. ** p < .01.
