AI-ASSISTED FEEDBACK AND ITS IMPACT ON EFL STUDENTS' WRITING DEVELOPMENT
Abstract
This article examines the impact of artificial intelligence-assisted feedback on the writing development of English as a Foreign Language (EFL) students at the university level. Drawing on four years of classroom teaching experience and an emerging body of research at the intersection of applied linguistics, educational technology, and writing pedagogy, the study investigates how AI-powered writing tools — including automated writing evaluation systems, large language model-based feedback platforms, and grammar and style checkers — reshape the feedback cycle in EFL writing instruction. The article presents a theoretically grounded analysis of AI feedback's distinct characteristics — immediacy, scalability, consistency, and multi-dimensional coverage — and evaluates both its advantages over and limitations compared to traditional teacher feedback. Practical classroom-based strategies for integrating AI feedback pedagogically and transparently are described, and classroom evidence with quantifiable outcomes is presented. The article argues that AI-assisted feedback, when implemented critically and in thoughtful combination with teacher and peer feedback, significantly accelerates EFL students' writing development by increasing the frequency, specificity, and actionability of the feedback they receive — provided that educators maintain a central role in shaping how students interpret and respond to AI-generated commentary.
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References
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