Optimising the number of course sections given optimal course sequence to support student retention
by Akash Gupta; Amir Gharehgozli; Seung-Kuk Paik
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 21, No. 4, 2022

Abstract: Although higher education institutions strive to create the environments that foster student retention, many students depart before graduation. Therefore, it is paramount to understand important factors that derive students retention. We observed that student retention is tied to the student grade point average (GPA) and, subsequently, the GPA is co-related to the order in which student enroll in courses. In this study, initially using statistical methods, we determine the best order of taking core courses. Then, we develop a prescriptive model using a mixed-integer linear programming. This model determines the optimal number of sections to be offered for each course so that maximum students can follow the optimal course order in a resource constrained environment. We also propose heuristic subroutines to solve the proposed model and determine the optimal number of sections for each course. In addition, we highlight the social and demographics factors that influence student retention. This study helps college administration to plan courses so that student retention can be improved.

Online publication date: Thu, 27-Oct-2022

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