Learners’ Collaboration With AI in Enhancing Peer Feedback in Argumentative Writing: An Exploratory Study

• In Event: Human–AI Collaboration in Learning: Dialogue, Inquiry, and Facilitation Patterns

Abstract

Peer feedback is an effective pedagogical strategy for improving argumentative writing, yet the integration of generative AI as a collaborator into this process remains underexplored. This study examines how AI-directed (explicit revisions) and AI-assisted (implicit suggestions and encouragement) peer feedback affect argumentative writing and feedback characteristics through an experiment among 90 university students. Content analysis revealed that AI-supported peer feedback enhances elaboration of writing. Epistemic Network Analysis showed that AI-assisted condition fostered integration of cognitive (problem identification, elaboration) and affective (mitigation, hedging) elements, whereas AI-directed condition yielded more structured, task-focused revisions. These findings highlight the impacts of AI support on peer feedback characteristics and argumentative writing, underscoring the importance of cognitive efficiency and socio-emotional engagement in AI-supported peer feedback.

Authors

• Wenli Chen, Nanyang Technological University - National Institute of Education

• Xuanyu Chen, Fudan University

• Lishan Zheng, Nanyang Technological University - National Institute of Education

• Qianru Lyu, Nanyang Technological University - National Institute of Education

• Guo Su, Nanyang Technological University - National Institute of Education

• Xinmei Kong, Nanyang Technological University - National Institute of Education