Students' Perceptions of AI-Powered Feedback in English Writing: Benefits and Challenges in Higher Education

Abstract

Collaboration between humans and artificial intelligence (AI) has the power to transform education, but research has yet to fully address how students engage cognitively with AI-powered feedback. Although studies suggest that AI can improve writing, few explore how students perceive and interact with AI tools. To fill this gap, the present study investigated Chinese university students' perceptions and experiences of using AI-powered English writing feedback tools: automated writing evaluation, generative AI, and corpora. Two hundred and ten student reflective journals were subjected to qualitative thematic analysis using NVivo software, along with analysis of classroom observations and students' writing. The students evaluated AI-powered feedback tools in three dimensions: content quality, delivery method, and overall effectiveness. They felt that these tools provided better grammar correction, instant feedback delivery, and an enhanced user experience, but challenges included vague explanations, limited emotional connection, and risks of overreliance. Based on these insights, this study introduces the Student-Teacher-AI Collaboration Model for feedback writing, which is designed to enhance collaboration between students, teachers, and AI in foreign language education. The findings have practical implications for the integration of AI tools into writing instruction and will inform policymaking in the rapidly evolving educational field. Received: 6 March 2025 | Revised: 6 May 2025 | Accepted: 30 May 2025 Conflicts of Interest The author declares that she has no conflicts of interest to this work. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. Author Contribution Statement Qianshan Chen: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Project administration, Funding acquisition.

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