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Collaborative argumentation enables students to build disciplinary knowledge and to think in disciplinary ways. We use Large Language Models (LLMs) to improve existing methods for collaboration classification and argument identification. Results suggest that LLMs are effective for both tasks and should be considered as a strong baseline for future research.
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This content will become publicly available on October 27, 2026
Using Large Language Models to Analyze Students’ Collaborative Argumentation in Classroom Discussions
Collaborative argumentation enables students to build disciplinary knowledge and to think in disciplinary ways. We use Large Language Models (LLMs) to improve existing methods for collaboration classification and argument identification. Results suggest that LLMs are effective for both tasks and should be considered as a strong baseline for future research.
more »
« less
- Award ID(s):
- 1917673
- PAR ID:
- 10656630
- Publisher / Repository:
- National Council on Measurement in Education (NCME). https://aclanthology.org/2025.aimecon-main.13.pdf
- Date Published:
- Volume:
- 1
- Page Range / eLocation ID:
- 111-125
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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