From Misunderstandings to Learning Opportunities: Leveraging Generative AI in Discussion Forums to Support Student Learning
Date
2025
Authors
Pozdniakov, S.
Brazil, J.
Poquet, O.
Krusche, S.
Berrezueta Guzman, S.
Sadiq, S.
Khosravi, H.
Editors
Cristea, A.I.
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Book chapter
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Source details - Title: Artificial Intelligence in Education. AIED 2025, 2025 / Cristea, A.I. (ed./s), vol.15882 LNAI, Ch.38, pp.291-298
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Abstract
In the contemporary educational landscape, particularly in large classroom settings, discussion forums have become a crucial tool for promoting interaction and addressing student queries. These forums foster a collaborative learning environment where students engage with both the teaching team and their peers. However, the sheer volume of content generated in these forums poses two significant interconnected challenges: How can we effectively identify common misunderstandings that arise in student discussions? And once identified, how can instructors use these insights to address them effectively? This paper explores the approach to integrating large language models (LLMs) and Retrieval-Augmented Generation (RAG) to tackle these challenges. We then demonstrate the approach Misunderstanding to Mastery (M2M) with authentic data from three computer science courses, involving 1355 students with 2878 unique posts, followed by an evaluation with five instructors teaching these courses. Results show that instructors found the approach promising and valuable for teaching, effectively identifying misunderstandings and generating actionable insights. Instructors highlighted the need for more fine-grained groupings, clearer metrics, validation of the created resources, and ethical considerations around data anonymity.
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Copyright 2025 The Author(s), under exclusive license to Springer Nature Switzerland