ROLE OF GOAL-SETTING AND PLANNING ON STUDENTS’ ACADEMIC PERFORMANCE OF COMPUTATIONAL MATHEMATICS: A BAYESIAN INFERENCE APPROACH

Authors

  • Huma Akram North China University of Water Resources and Electric Power, Zhengzhou, Author
  • Ayesha Sohail School of Mathematics and Statisitcs, University of Sydney, Australia. Author

Keywords:

Bayesian inference, e-portfolios, goal setting, planning, Computational Mathematics

Abstract

The ability to set academic goals and plan strategies to achieve them has been postulated for a long time as a
predictor of academic success. Despite its recognition, its distinctive place in the context of computational
mathematics is yet to be fully investigated. Grounded in self-regulated learning (SRL), this study investigates the
critical role of goal-setting and planning in enhancing mathematics learning, particularly in programming-based
contexts. Applying Bayesian inference, the study models individual learning processes, offering personalized insights
for effective educational interventions. Based on the analysis, the implementation of e-portfolios was found
instrumental in fostering goal-setting and planning skills among students. The findings highlight the need for
interactive, technology-enhanced teaching approaches to keep students engaged and motivated at the university
level. Additionally, key implications are presented to relevant stakeholders.

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Author Biographies

  • Huma Akram, North China University of Water Resources and Electric Power, Zhengzhou,

    School of International Education, North China University of Water Resources and Electric Power, Zhengzhou, Henan, China. akramhuma@ncwu.edu.cn

  • Ayesha Sohail, School of Mathematics and Statisitcs, University of Sydney, Australia.

    School of Mathematics and Statisitcs, University of Sydney, Australia.

Published

2025-01-11

Issue

Vol. 4 No. 04 (2024): EDUCATIONAL RESEARCH AND INNOVATION

Section

Articles