The Impact of GenAI Feedback on Chinese EFL Students’ Emotional Engagement: A Mixed Effect Modelling Approach

Abstract The role of GenAI in learners’ emotional engagement has become an increasingly relevant topic in recent times, particularly in how it shapes learners’ interactions with and processing of written feedback. The present study explores the effectiveness of peer feedback compared to GenAI feedback in EFL writing context. Participants ( n = 152) were first-year undergraduate students at a Chinese university enrolled in an English writing course. The peer feedback group ( n = 78) received feedback from peers, while the GenAI group ( n = 74) utilized ChatGPT with carefully crafted prompts for writing feedback. A survey measuring emotional engagement—including emotional connections, sense of belonging, motivation and enthusiasm, and emotional reactions—was administered at the beginning and end of the semester. Mixed effects modelling was used for data analysis. Results indicated that all four types of emotional engagement were significantly higher in the GenAI group, with particularly pronounced outcomes in emotional connections, sense of belonging, and motivation and enthusiasm. These findings suggest that while GenAI feedback can be effectively integrated into EFL writing instruction, its combination with human interaction remains crucial. In particular, learners’ emotional reaction to GenAI use is a key issue. The study concludes with pedagogical implications for leveraging GenAI in EFL writing contexts.