A Recommender System for Personalized Exploration of Majors, Minors, and Concentrations

Many students change their majors during college. Choosing the right academic majors, minors, and concentrations within a major in higher education is challenging but crucial in assuring students’ overall academic and career success. Personalized prediction of student success in majors, minors, and concentrations will help students better find the right majors, minors, and concentrations for them, so as to timely achieve their academic goals. In this paper, we present a new recommender application for the academic major/minor/concentration selection problem in the educational domain. The proposed major/minor/concentration recommender system is a collaborative filtering-based recommender based on student grade prediction, and provides a variety of personalized predictions and recommendations on majors, minors, and concentrations. It is a useful tool to guide students, advisors, and administrators during the personalized major/minor/concentration exploration (declare/change) process.