Urban Adolescents' Motivation Profiles in Physical Education

Purpose

With the belief that theoretical integration in motivation may help us better understand students' motivational behaviors, we designed this study to explore urban adolescents' motivation profiles and their relationships with learning and leisure-time physical activity during a three-month physical education personal conditioning unit.

Methods

Middle school students from a large urban inner-city school district (N = 603, age range=11-15 years, mean age=12.4 years) completed questionnaires assessing the following motivation constructs: achievement goals (i.e., mastery and performance goals), task value (i.e., perceived importance, interest, and usefulness), and psychological need satisfactions (i.e., perceived autonomy, competence, and relatedness) in physical education. In-class effort and knowledge were measured using teachers' ratings and a validated knowledge test, respectively. Physical activity level in leisure time was assessed with a 4-item Leisure-Time Exercise Questionnaire (Godin & Shephard, 1986).

Analysis/Results

Using hierarchical cluster analysis, we found that students' motivation in physical education was multi-dimensional with three distinct clusters. Cluster 1 included 253 students who had the highest scores on perceived autonomy, relatedness, and interest. Cluster 2, by comparison, consisted of 191 students with relatively low perceived autonomy, but high performance goals. Cluster 3 included 159 students with the lowest scores in most motivation constructs. To understand the differences among the clusters, we conducted a MANOVA with the cluster groups as the independent variables and the motivational constructs as the dependent variables. Results of the MANOVA indicated significant overall differences among clusters, Wilks' Ë=.12, F (18, 1184) = 123.57, p<.00. Univariate follow-ups revealed that the clusters were significantly different on all dependent variables. Further, we conducted another MANOVA to test the predictive role of the cluster solution on in-class effort, knowledge, and leisure-time physical activity. The results showed significant differences between the three clusters. Wilks' Ë=.85, F (6, 1196) = 12.60, p<.00. Based on post hoc analyses, students in cluster 1 had the highest scores in all variables. Students in cluster 2 had higher leisure-time physical activity levels than did cluster 3.

Conclusions

These findings suggest that students' development in physical education may depend upon a collective impact of changes in knowledge, physical activity involvement, and sources of motivation. Physical educators should understand that each student in physical education manifests a different motivation profile associated with their knowledge and experiences. Individual differences in physical education should be identified, appreciated, and instructionally addressed during the learning process.