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Validity and reliability evaluation of the 2 x 2 perceived motivational climate questionnaire in physical activity settings.

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

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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.
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Date:Dec 1, 2015
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