Assessing impact of problem-based learning using data mining to extract learning patterns
Journal of Applied Research in Higher Education
ISSN: 2050-7003
Article publication date: 26 June 2023
Issue publication date: 5 March 2024
Abstract
Purpose
This paper defines and assesses student learning patterns under the influence of problem-based learning (PBL) and their classification into a reasonable minimum number of classes. Study utilizes PBL implemented in an undergraduate Statistics and Operations Research course for techno-management students at a private university in India.
Design/methodology/approach
Study employs an in situ experiment using a conceptual model based on learning theory. The participant's end-of-semester GPA is Performance Indicator. Integrating PBL with classroom teaching is unique instructional approach to this study. An unsupervised and supervised data mining approach to analyse PBL impact establishes research conclusions.
Findings
The administration of PBL results in improved learning patterns (above-average) for students with medium attendance. PBL, Gender, Math background, Board and discipline are contributing factors to students' performance in the decision tree. PBL benefits a student of any gender with lower attendance.
Research limitations/implications
This study is limited to course students from one institute and does not consider external factors.
Practical implications
Researchers can apply learning patterns obtained in this paper highlighting PBL impact to study effect of every innovative pedagogical study. Classification of students based on learning behaviours can help facilitators plan remedial actions.
Originality/value
1. Clustering is used to extract student learning patterns considering dynamics of student performances over time. Then decision tree is utilized to elicit a simple process of classifying students. 2. Data mining approach overcomes limitations of statistical techniques to provide knowledge impact in presence of demographic characteristics and student attendance.
Keywords
Acknowledgements
We thank unknown reviewers for their valuable inputs and Mr. Girish Manghani for his help in improving the English of the research paper.
Citation
Mujumdar, S.B., Acharya, H., Shirwaikar, S. and Bafna, P.B. (2024), "Assessing impact of problem-based learning using data mining to extract learning patterns", Journal of Applied Research in Higher Education, Vol. 16 No. 2, pp. 610-628. https://doi.org/10.1108/JARHE-05-2022-0165
Publisher
:Emerald Publishing Limited
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