81. Courselect: Motivation-Centric Course Recommendation for University Students

University students enrolled in academic programs across the globe face a common problem at the onset of each semester–figuring out which courses to register for. This paper presents qualitative interviews to identify the motivations of university students underlying course selection. The paper then proposes an algorithm for a course recommendation system ‘Courselect’ which helps students select courses based on their motivations. We also present a prototype web interface of the proposed system. The proposed algorithm models each agent in the university system as a node and provides course recommendations by minimizing the distance between relevant nodes. The web interface facilitates the course selection decision without undermining students’ freedom of choice. This paper argues that Courselect can be calibrated for any university-level academic model or e-learning application to improve the student experience of the academic system.