A MULTIVARIATE ANALYSIS OF ACADEMIC, BEHAVIORAL, AND PSYCHOLOGICAL PREDICTORS OF STUDENT PERFORMANCE
Abstract
This paper explores how academic, behavioral and psychological variables relate to student performance through amultivariate analytical approach.Theapproach used to examine 1,000 student observations was quantitative andexplanatory research. The independent variables considered were academic score, course participation, attendance rate,emotional engagement, physical activity, device usage, and feedback score. According to descriptive statistics, there wereconsiderable variations in all variables, and academic scores were normally distributed and hence could be subjected toparametric statistics. From the Pearson correlation, there were notable correlations between academic score and studentperformance (r = 0.926). However, other variables correlated weakly or insignificantly with student performance.Multiple regression results indicated that academic score was the only statistically significant predictor of student performance (β = 0.926, p < 0.001), explaining a high proportion of the variation in the performance of students (R² = 0.858). In addition, behavioral and psychological variables did not have any significant effect on the dependent variablein the model.The study highlights the importance of adopting comprehensive analytical approaches to better understandthe complex interplay of factors affecting student outcomes and provides valuable insights for educators and policymakersaiming to improve educational effectiveness.
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References
Astin, A. W. (2014). Student involvement: A developmental theory for higher education. In College student
development and academic life (pp. 251-262). Routledge.
Baeten, M., Dochy, F., & Struyven, K. (2013). The effects of different learning environments on students’ motivation
for learning and their achievement. British journal of educational Psychology, 83(3), 484-501.
Bénabou, R., & Tirole, J. (2016). Mindful economics: The production, consumption, and value of beliefs. Journal of
Economic Perspectives, 30(3), 141-164.
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher
education learning environments: A systematic review. The internet and higher education, 27, 1-13.
Carter Jr, R. A., Rice, M., Yang, S., & Jackson, H. A. (2020). Self-regulated learning in online learning environments:
strategies for remote learning. Information and Learning Sciences, 121(5-6), 321-329.
Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A
developmental, social cognitive, and sociocultural perspective on motivation. Contemporary educational
psychology, 61, 101859.
Finn, J. D., & Zimmer, K. S. (2012). Student engagement: What is it? Why does it matter?. In Handbook of research
on student engagement (pp. 97-131). Boston, MA: Springer US.
Fredricks, J. A., Filsecker, M., & Lawson, M. A. (2016). Student engagement, context, and adjustment: Addressing
definitional, measurement, and methodological issues. Learning and instruction, 43, 1-4.
Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on
intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & education, 80,
-161.
Hattie, J. (2015). The applicability of visible learning to higher education. Scholarship of teaching and learning in
psychology, 1(1), 79.
Jang, H., Kim, E. J., & Reeve, J. (2016). Why students become more engaged or more disengaged during the semester:
A self-determination theory dual-process model. Learning and instruction, 43, 27-38.
Junco, R. (2015). Student class standing, Facebook use, and academic performance. Journal of Applied Developmental
Psychology, 36, 18-29.
Kahu, E. R. (2013). Framing student engagement in higher education. Studies in higher education, 38(5), 758-773.
Kuh, G. D., & O'Donnell, K. (2013). Ensuring quality and taking high-impact practices to scale. Peer Review, 15(2),
-33.
Lei, H., Cui, Y., & Zhou, W. (2018). Relationships between student engagement and academic achievement: A metaanalysis. Social Behavior and Personality: an international journal, 46(3), 517-528.
Lepp, A., Barkley, J. E., & Karpinski, A. C. (2014). The relationship between cell phone use, academic performance,
anxiety, and satisfaction with life in college students. Computers in human behavior, 31, 343-350.
Martin, A. J. (2012). Academic Buoyancy and Academic Resilience.
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in
psychology, 8, 422.
Reeve, J. (2024). Understanding motivation and emotion. John Wiley & Sons.
Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students' academic
performance: a systematic review and meta-analysis. Psychological bulletin, 138(2), 353.
Salmela-Aro, K., & Upadyaya, K. (2020). School engagement and school burnout profiles during high school–The
role of socio-emotional skills. European Journal of Developmental Psychology, 17(6), 943-964.
Schneider, M., & Preckel, F. (2017). Variables associated with achievement in higher education: A systematic review
of meta-analyses. Psychological bulletin, 143(6), 565.
Snyder, K. E., Malin, J. L., Dent, A. L., & Linnenbrink-Garcia, L. (2014). The message matters: The role of implicit
beliefs about giftedness and failure experiences in academic self-handicapping. Journal of Educational
Psychology, 106(1), 230.
Talsma, K., Robertson, K., Thomas, C., & Norris, K. (2021). COVID-19 beliefs, self-efficacy and academic
performance in first-year university students: cohort comparison and mediation analysis. Frontiers in Psychology, 12,
Trolian, T. L. (2023). Student engagement in higher education: Conceptualizations, measurement, and research.
In Higher Education: Handbook of Theory and Research: Volume 39 (pp. 1-60). Cham: Springer Nature Switzerland.
Zimmerman, B. J. (2015). Self-regulated learning: Theories, measures, and outcomes.
Ziya. (n.d.). Personalized educational dataset [Data set]. Kaggle.
https://www.kaggle.com/datasets/ziya07/personalized-educational-dataset
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