Algorithms for dividing students into study groups

Abstract

Importance: After the first or second year of study, students in a specific field, such as «Economics», are assigned to specialized tracks, for example, «Finance and Credit» or «Enterprise and Organizational Economics». Once students are distributed across these tracks, it becomes necessary to form study groups. Purpose: To develop algorithms for assigning students to study groups within a track based on two optimization criteria: Maximizing the «similarity» of average academic scores across groups within the same track. Maximizing the «similarity» of group distribution to the previous one. Research design: Development of algorithms for distributing students into specialized study groups based on four optimization criteria: maximizing the «similarity» of the total and average scores within groups of the same profile, maximizing the «similarity» of academic performance among students within each group, and maximizing the «similarity» of distribute on compared to previous groupings. Results: For each problem, mixedinteger programming models were formulated, along with greedy heuristic algorithms. The mathematical models and algorithms were tested on realworld data from Saint Petersburg State University of Economics when distributing students in the «Economics» program.