Abstract

This study investigates how English as a foreign language (EFL) student reviewers engage in open-ended, dialogic interactions with generative artificial intelligence (AI) during the feedback generation process in peer assessment within EFL writing classrooms. It examines the impact of these interactions on feedback quality perceived by recipients, emotional responses (task enjoyment and anxiety), and feedback literacy. A quasi-experimental design was employed with 60 Chinese undergraduate students, divided into an experimental group (EG) that used generative AI (Doubao) for support and a control group (CG) that did not. Over three intervention cycles, data from chat histories, feedback quality ratings by recipients, and pre/post questionnaires on emotions and feedback literacy were analyzed. The results indicated that EG students primarily employed AI for linguistic refinement of their comments, with limited use for enhancing the content or structure. Nevertheless, AI support led to significant, progressive improvements in the perceived quality of feedback, particularly in affect, description, justification, and constructiveness. Furthermore, EG students reported significantly higher task enjoyment and lower anxiety compared to the CG. The intervention also positively enhanced all dimensions of feedback literacy: knowledge and abilities, willingness to participate, cooperative learning, and appreciation of peer feedback. The findings suggest that generative AI can serve as a powerful scaffold, reducing the emotional and cognitive burdens of peer assessment while fostering a more supportive and effective feedback environment. This study underscores the value of integrating AI into peer feedback practices to develop students’ feedback literacy and improve the overall quality of peer learning experiences.

Journal
Assessing Writing
Published
2026-10-01
DOI
10.1016/j.asw.2026.101100
CompPile
Open Access
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