QUALITY Physical Education, Learning Styles, and Motivation of College Students in Physical Education Classes: An Explanatory Sequential DESIGN
Keywords:
Education, Quality Physical Education, Learning Styles, Motivation, explanatory sequential design, PhilippinesAbstract
This study explored the influence of quality physical education (QPE) and learning styles on college students’ motivation in physical education (PE) using a mixed methods approach, particularly explanatory sequential design. For the quantitative phase, respondents were randomly chosen from among the selected higher education institution in Region XII, and for the qualitative phase, participants were purposively chosen from the respondents of the quantitative phase to participate in the in-depth interview and focus group discussion. Sets of adapted survey tools and an interview guide were used to gather data. The mean, standard deviation, and linear regression were used as statistical tools for the quantitative strand. Further, coding and thematic analysis were employed for the qualitative strand. Findings revealed high mean ratings in QPE, learning styles and colleges students’ motivation in physical education respectively. Furthermore, QPE and learning styles were both found as significant predictors of college students’ motivation in physical education. Moreover, results showed that the high percentage of the variance of the college student motivation in PE was explained by the independent variables, QPE, and learning styles, thus it can be said that a certain percentage of the variance can be attributed to other factors aside from the variables explored in the study. The combined influence of quality physical education and learning styles as predictors of motivation in physical education among college students was a good fit for the data in this study. Also, the participants' standpoints on the salient findings of the study were probed for further explanation in the qualitative strand. Thus, the joint display revealed the confirming-merging nature of data integration.