Abstract
The current study examines the effectiveness of problem-based learning for a select variable related to learning. This study identifies the average distance between control groups and experimental groups based on several dimensions (or variables) that are not necessarily independent, and the main dimensions that create the distance between experimental groups and experimental groups. We also examined whether the gap between the groups was statistically significant. The study was experimental in nature and research design of the pre-and post-test control group research was employed. For this purpose, a sample of 486 students were obtained by using matching with random assignment techniques. Seven variables- gender, intelligence, self-efficacy, self-regulatory, achievement, meta-cognitive knowledge and meta-cognitive regulation – have been taken into account. The obtained data were analyzed with discriminant analysis of winning scores. The findings of the study indicate that achievement in economics is one of the most important variables contributing significantly to the differences between experimental and control groups and self-regulated learning contributes the least to the differences between the two groups (experimental groups and control groups).
Keywords: Problem-Based Learning, Metacognition, Achievement, Self-Efficacy, Self-Regulation, Discriminant Analysis
CITE THIS PAPER
APA Format:
Kaur, A. (2025). Data driven insights into problem-based learning: A discriminant analysis on key learner variables. Journal of Pedagogical Innovations and Teacher Education, 2(1), 89–101. https://jpita.mitc.ac.in/2025/06/05/amandeepkaur/
MLA Format:
Kaur, Amandeep. “Data Driven Insights into Problem-Based Learning: A Discriminant Analysis on Key Learner Variables.” Journal of Pedagogical Innovations and Teacher Education, vol. 2, no. 1, 2025, pp. 89–101. https://jpita.mitc.ac.in/2025/06/05/amandeepkaur/
Chicago/Turabian Format:
Kaur, Amandeep. “Data Driven Insights into Problem-Based Learning: A Discriminant Analysis on Key Learner Variables.” Journal of Pedagogical Innovations and Teacher Education 2, no. 1 (2025): 89–101. https://jpita.mitc.ac.in/2025/06/05/amandeepkaur/
Harvard Style:
Kaur, A., 2025. Data driven insights into problem-based learning: A discriminant analysis on key learner variables. Journal of Pedagogical Innovations and Teacher Education, 2(1), pp.89–101. Available at: https://jpita.mitc.ac.in/2025/06/05/amandeepkaur/
IEEE Format:
A. Kaur, “Data driven insights into problem-based learning: A discriminant analysis on key learner variables,” Journal of Pedagogical Innovations and Teacher Education, vol. 2, no. 1, pp. 89–101, 2025. [Online]. Available: https://jpita.mitc.ac.in/2025/06/05/amandeepkaur/