Comparative review reports student performance prediction approaches in higher education, highlighting optimal modeling strategies for institutional quality improvement.
Higher education quality (HEQ) stakeholders increasingly see the student as the core of the teaching operation. To improve HEQ a good prediction of students’ performance is a considerable step. In this paper we discuss the use of two approaches used in the literature in students’ performance (SP) prediction: Machine Learning (ML) techniques and Fuzzy Cognitive Mapping (FCM). Our main contribution is a comparative analysis of these approaches and recommendations in context of the Moroccan Higher Education institutions.
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Oqaidi et al. (2022) studied this question.
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