Designing the architecture of an intelligent decision support system for course selection based on ontologies

Abstract

The increasing diversity of elective courses in curricula amid the digital transformation of universities exacerbates the problem of creating individual educational plans, as students face information overload and difficulty adhering to academic rules. Conventional statistically based recommender systems do not explain their decisions and ignore prerequisites and schedules. The goal of our paper is to design the architecture of an intelligent decision support system for course selection based on an ontological approach. In this paper, we presented a modular system structure in which modules for ontology preparation, student profile creation, rule checking, and meaningful course selection operate in a chain. We demonstrated that the ontological approach enables clear definition of disciplines, professional skills, and educational requirements. We found that the integration of logical rules and semantic analysis ensures rigorous verification of prerequisites and schedules while maintaining the flexibility of searching for suitable courses. We also demonstrated that the proposed architecture solves the problem of understanding by generating a clear explanation for each recommendation using educational language. The implementation of the proposed architecture will reduce the workload of teachers and improve the quality of independent course selection by students.