Chinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia

• Postgraduates engaged behaviorally, affectively, and cognitively with GenAI feedback. • Postgraduates dealt with ChatGPT primarily as a tool for refining their proposals, not for generating content. • Postgraduates demonstrated agency by actively questioning, annotating, and negotiating feedback. • Postgraduates engaged in diverse affective responses, ranging from appreciation to frustration. As Generative artificial intelligence (GenAI) tools such as ChatGPT are becoming increasingly integrated into English as a Foreign Language (EFL) academic writing context, learners’ engagement with AI-generated feedback remains insufficiently examined. This case study investigated how four Chinese EFL postgraduates joining a course in a Malaysian university engaged with ChatGPT feedback while revising their academic research proposals. The study triangulated screen recordings, pre- and post-revision drafts, and stimulated recall interviews. Participants displayed a range of behavioural strategies, including accepting, questioning, rejecting suggestions, annotating visually, and seeking external validation. Affective responses ranged from appreciation and curiosity to doubt and frustration, particularly when feedback appeared conflicting or imprecise. Cognitively, learners applied various strategies such as evaluating, comparing, negotiating feedback, and regulating its use. Yet, they showed differing levels of engagement, shaped by individual perceptions and writing intentions. Importantly, participants regarded ChatGPT as a tool for linguistic refinement rather than content generation. Overall, the findings revealed that learners did not passively receive feedback but interacted with it in agentive and critical ways. The study highlights the interplay among these three dimensions of engagement and the importance of individual differences when evaluating the pedagogical potential of GenAI-generated feedback in academic writing.

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Publication Details

Journal
Computers & composition/Computers and composition
Published
2025-12-26
DOI
https://doi.org/10.1016/j.compcom.2025.102976
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
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article

Chinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia

Zhang Kailin
1 citations
Computers & composition/Computers and composition
Artificial Intelligence in Healthcare and Education
0.65
article

Chinese EFL learners’ engagement with ChatGPT feedback on academic writing: A case study in Malaysia

Zhang Kailin
article en
1 citations

Abstract

• Postgraduates engaged behaviorally, affectively, and cognitively with GenAI feedback. • Postgraduates dealt with ChatGPT primarily as a tool for refining their proposals, not for generating content. • Postgraduates demonstrated agency by actively questioning, annotating, and negotiating feedback. • Postgraduates engaged in diverse affective responses, ranging from appreciation to frustration. As Generative artificial intelligence (GenAI) tools such as ChatGPT are becoming increasingly integrated into English as a Foreign Language (EFL) academic writing context, learners’ engagement with AI-generated feedback remains insufficiently examined. This case study investigated how four Chinese EFL postgraduates joining a course in a Malaysian university engaged with ChatGPT feedback while revising their academic research proposals. The study triangulated screen recordings, pre- and post-revision drafts, and stimulated recall interviews. Participants displayed a range of behavioural strategies, including accepting, questioning, rejecting suggestions, annotating visually, and seeking external validation. Affective responses ranged from appreciation and curiosity to doubt and frustration, particularly when feedback appeared conflicting or imprecise. Cognitively, learners applied various strategies such as evaluating, comparing, negotiating feedback, and regulating its use. Yet, they showed differing levels of engagement, shaped by individual perceptions and writing intentions. Importantly, participants regarded ChatGPT as a tool for linguistic refinement rather than content generation. Overall, the findings revealed that learners did not passively receive feedback but interacted with it in agentive and critical ways. The study highlights the interplay among these three dimensions of engagement and the importance of individual differences when evaluating the pedagogical potential of GenAI-generated feedback in academic writing.

Computers & composition/Computers and compositionVol. 79
University of Malaya (MY)
Quality Education
Openalex Percentile: Top 18%
Artificial Intelligence in Healthcare and Education
0.65
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