A Collaborative Approach for Course Recommendation System

Abstract

Graduate attributes are the competencies and capabilities set by the college network as benchmark for its students during their time with the organization. The principle point of the paper is to assist students with their scholastic choices, by suggesting elective courses dependent on the graduating attributes scores. Students rate the significance of each course in improving their graduating qualities toward the end of every semester. The elective courses taken by peer students and rated similarly are identified by a collaborative filtering algorithm and prescribed to students. This paper predicts the rating for each course and graduating attribute. The elective courses with the greatest expected ratings are shortlisted for proposal. Also, the aggregated GA score is determined for each student at end of every semester. The shortlisted courses that can improve the feeble GA scores are at prescribed to students.