The abundance of courses available in university and the highly personalized curriculum is often overwhelming for students who must select courses relevant to their academic interests. A large body of research in course recommendation systems focuses on optimizing prediction and improving accuracy. However, those systems usually afford little or no user interaction, and little is known about the influence of user-perceived aspects for course recommendations, such as transparency, controllability, and user satisfaction. In this paper, we argue that involving students in the course recommendation process is important, and we present an interactive course recommendation system that provides explanations and allows students to explore courses in a personalized way. A within-subject user study was conducted to evaluate our system and the results show a significant improvement in many user-centric metrics.
|CEUR Workshop Proceedings
|Published - 2021
|2021 Joint ACM Conference on Intelligent User Interfaces Workshops, ACMIUI-WS 2021 - College Station, United States
Duration: Apr 13 2021 → Apr 17 2021
All Science Journal Classification (ASJC) codes
- General Computer Science