ORIGINAL RESEARCH article
Front. Educ.
Sec. Higher Education
Course Evaluation Modeling Using Multi-Level Regression: A Case Study for a Master of Business Administration (MBA)
Provisionally accepted- 1University Canada West, Vancouver, Canada
- 2Gulf University for Science & Technology, Hawally, Kuwait
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Understanding and modelling course evaluation scores in higher education programs is crucial for enhancing and improving student experience and program outputs. This study investigates the influence of several factors related to course and instructor characteristics on the course evaluation scores in the Master of Business Administration (MBA) program. Course evaluation data from 1,639 course sections across 9 terms at a North American MBA program was used. The study utilized a multi-level regression model, which considers the hierarchal structure of the data and group-level heterogeneity, to model the course evaluation scores. The results show that larger class sizes correlate statistically with a lower evaluation score. Moreover, online classes received statistically lower evaluation scores than hybrid courses, which can be attributed to students' feelings of isolation due to reduced face-to-face connection. Permanent faculty tend to have a higher average evaluation score compared with sessional faculty. This research advances understanding of factors influencing MBA course evaluations and provides evidence-based guidance for improving teaching effectiveness and program design in professional graduate education.
Keywords: course evaluation, higher education, Multi-level regression model, Studentevaluation, Mba program
Received: 12 Aug 2025; Accepted: 24 Nov 2025.
Copyright: © 2025 Moshiri, Farhadian, Alsaleh and T. Alsaleh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Rushdi Alsaleh, rushdi.alsaleh@ubc.ca
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
