A Recommender System Architecture for University Curriculum Advising
This study proposes a goal-based agent recommender system for undergraduate students using a large language model, tailored to curriculum requirements, prerequisites, and student preferences. The system optimizes course selection, streamlines degree path exploration, and predicts enrollment metrics, reducing advisor workloads and promoting academic engagement, ultimately enhancing student success and increasing the overall academic achievement of the student body.
May 28, 2025
