Recommender Systems for Students’ Performance in Higher Educations: A Review

Student success is a primary strategic goal for most higher education institutions. With budget cuts and rising operating costs, higher education institutions are focusing more on retaining student enrollment in their programs while preserving educational quality. This motivates academics to develop the best way for predicting students' future success based on Recommender System, which aids students in their academic achievement. As a result, the primary goal of this study is to identify the most often investigated elements influencing student performance. In this research, 15 research articles were critically reviewed and analyzed. This review found that from the small amount of research, most studies use machine learning algorithms to find solutions to the problems. However, this article will look to find a method that may prove to be more effective. Finally, this article contributes to students' academic achievement via a recommender system and identifies the most successful machine learning methods.