Module Advisor: A Hybrid Recommender System for Elective Module Exploration
Refereed Conference Meeting Proceeding
Recommender systems are omni-present in our every day lives, guiding us through the vast amount of information available. However, in the academic world, personalised recommendations are less prominent, leaving students to navigate through the typically large space of available courses and modules manually. Since it is crucial for students to make informed choices about their learning pathways, we aim to improve the way students discover elective modules by developing a hybrid recommender system prototype that is specifically designed to help students find elective modules from a diverse set of subjects. We can improve the discoverability of long-tail options and help students broaden their horizons by combining notions of similarity and diversity.
12th ACM Conference on Recommender Systems
Digital Object Identifer (DOI):
National University of Ireland, Dublin (UCD)
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