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Recommendation System of Subjects in the Registration and Enrollment Process of University Students

Abstract:

Currently, recommendation systems are widely used to analyze user preferences and suggest related items. At the university level, the moment in which a subject is chosen by a student for his next educational stage, is monitored by an Academic Counselor, who according to the student record, and comparing similar profiles throughout his career, must recommend which subjects could contribute to student performance and learning. The present work represented an effort to design a recommender that is based on the modeling of the causal relationships existing between the subjects of the curricular curriculum of a university career, using fuzzy cognitive maps and OWA aggregation operators. The workflow of the proposed model and its implementation were applied through the computer tool (FCMDecision). A case study with the student records of a university in Guayaquil was developed, and an experiment was also carried out to test interpretability results with other existing models. Among the main results are the reliability of the metrics for the static analysis of fuzzy maps, the similarity with respect to a target student, and the importance that each subject represents in a new record.