Evaluating a GPT-4 and Retrieval-Augmented Generation-Based Conversational Agent to Enhance Learning Experience in a MOOC [r-libre/3602]

Miladi, Fatma; Psyché, Valéry; Diattara, Awa; El Mawas, Nour, & Lemire, Daniel (In Press). Evaluating a GPT-4 and Retrieval-Augmented Generation-Based Conversational Agent to Enhance Learning Experience in a MOOC. In 17th International Conference on Computer Supported Education.

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Item Type:	Papers in Conference Proceedings
Refereed:	Yes
Status:	In Press
Abstract:	Massive Open Online Courses (MOOCs) face significant challenges due to low completion rates, primarily caused by insufficient personalized support for learners. To address this, we developed a pedagogical AI-powered conversational agent enhanced with Retrieval-Augmented Generation (RAG) to provide real-time, contextually relevant support. Our evaluation with 25 learners demonstrated a statistically significant knowledge gain in the experimental group compared to the control group. Additionally, the agent achieved a high System Usability Scale (SUS) score. These findings highlight the potential of AI technologies to enhance online learning environments and inform future research on their role as learning companions in distance education.
Depositor:	Lemire, Daniel
Owner / Manager:	Daniel Lemire
Deposited:	11 Feb 2025 15:39
Last Modified:	11 Feb 2025 15:39

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