Predicting Student Success in Online Physical Education

Abstract

(i.e. study environment). Lastly, a direct binary logistic regression was performed to assess the impact of significant factors from the previous analysis on the likelihood that student would complete or not complete an online HRF course. Results: The model contained 6 independent variables (GPA, class standing, hours worked outside of school, achievement, organization and study environment). The full model containing all predictors was statistically significant (χ 2 (6, N=821) = 94.296, p<.001), indicating that the model was able to distinguish between students who completed and did not complete the online HRF course. Four of the independent variables made a unique statistically significant contribution to the model: (1) GPA, (2) Class Standing, (3) Hours Worked Outside of School and (4) Organization. The strongest predictor of a course completion were student who reported entering the course with a GPA of 2.6-4.0, recording an odds ratio of 3.96. This indicated that students who entered the course with a GPA above a 2.6 were almost 4 times more likely to complete an online HRF course than those who entered with a lower GPA, controlling for all other factors in the model. Conclusion: Upon course entry, students who did not complete the course generally reported a combination of the following factors: GPA below 2.6, worked more than 20 hours outside of school, underclassman class standing, and reported weak organizational beliefs. This analysis provides an initial understanding of the unique student characteristics affecting online HRF course completion. been invaluable. I would also like to thank my committee members, Dr. Eloise Elliott, Dr. Barbara Lublow, and Dr. David Daum for serving on my committee: thank you all of your guidance over the years. Without all of your supervision and constant help this dissertation would not have been possible.

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