Multi-agent debate in L2 argumentative writing: An exploratory study of Chinese EFL learners

Argumentative writing poses significant challenges for second-language (L2) learners. Generative AI (GenAI) offers pedagogical support, but existing tools typically act as single assistants and fail to simulate the dynamic, multi-perspective dialogue essential for robust argumentation. We introduce a Multi-Agent Debate (MAD) framework in which multiple AI personas engage in structured debates to foster divergent thinking and expose learners to varied viewpoints. In a one-group pretest–posttest exploratory study (N = 22 Chinese EFL undergraduates), we investigated MAD’s impact on argumentative writing and learner perceptions. Preliminary results indicate that MAD enhanced argument structure and quality, promoted metacognitive awareness, cultivated critical AI skepticism, and reduced anxiety when addressing controversial topics. These findings suggest MAD is a promising approach for improving both L2 argumentative skills and GenAI literacy.

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Publication Details

Journal
Proceedings of the International CALL Research Conference
Published
2025-09-30
DOI
https://doi.org/10.29140/97817637116240-03
Primary Topic
Language, Metaphor, and Cognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Multi-agent debate in L2 argumentative writing: An exploratory study of Chinese EFL learners

Tianshu Chu
Proceedings of the International CALL Research Conference
Language, Metaphor, and Cognition
article

Multi-agent debate in L2 argumentative writing: An exploratory study of Chinese EFL learners

Tianshu Chu
article en

Abstract

Argumentative writing poses significant challenges for second-language (L2) learners. Generative AI (GenAI) offers pedagogical support, but existing tools typically act as single assistants and fail to simulate the dynamic, multi-perspective dialogue essential for robust argumentation. We introduce a Multi-Agent Debate (MAD) framework in which multiple AI personas engage in structured debates to foster divergent thinking and expose learners to varied viewpoints. In a one-group pretest–posttest exploratory study (N = 22 Chinese EFL undergraduates), we investigated MAD’s impact on argumentative writing and learner perceptions. Preliminary results indicate that MAD enhanced argument structure and quality, promoted metacognitive awareness, cultivated critical AI skepticism, and reduced anxiety when addressing controversial topics. These findings suggest MAD is a promising approach for improving both L2 argumentative skills and GenAI literacy.

Proceedings of the International CALL Research ConferenceVol. 2025
Capital Normal University (CN)
Openalex Percentile: Top 71%
Language, Metaphor, and Cognition
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