36 citations · 61 across the 9 of their papers we have counts for
4 papers · 1 filter
iLLuMinaTE: An LLM-XAI Framework Leveraging Social Science Explanation Theories Towards Actionable Student Performance Feedback
Vinitra Swamy, Davide Romano, Bhargav Srinivasa Desikan +2
Recent advances in eXplainable AI (XAI) for education have highlighted a critical challenge: ensuring that explanations for state-of-the-art AI models are understandable for non-te…
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
Beatriz Borges, Negar Foroutan, Deniz Bayazit +87
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they a…
Course Recommender Systems Need to Consider the Job Market
Jibril Frej, Anna Dai, Syrielle Montariol +2
Current course recommender systems primarily leverage learner-course interactions, course content, learner preferences, and supplementary course details like instructor, institutio…
Towards Modeling Learner Performance with Large Language Models
Seyed Parsa Neshaei, Richard Lee Davis, Adam Hazimeh +3
Recent work exploring the capabilities of pre-trained large language models (LLMs) has demonstrated their ability to act as general pattern machines by completing complex token seq…