AI-GENERATED PERSONALIZED FEEDBACK IN EFL WRITING: EFFECTS ON REVISION QUALITY AND LEARNER ENGAGEMENT

Abstract

The integration of artificial intelligence (AI) into language education has created new opportunities to provide timely, individualized feedback in second-language writing instruction. This study investigates the impact of AI-generated personalized feedback on EFL students’ writing development, revision behavior, and learner Engagement. Using a mixed-method quasi-experimental design, the study involved 120 undergraduate EFL students divided into an experimental group receiving AI-generated feedback and a control group receiving conventional teacher feedback. Data were collected through pre-test and post-test writing tasks, revision analysis, Engagement questionnaires, and semi-structured interviews. Quantitative analysis showed that students who received AI-generated feedback demonstrated greater improvement in writing performance, particularly in grammar accuracy and text organization. Students in the AI feedback group also performed more frequent and deeper revisions, including meaning-level revisions such as paragraph restructuring and argument development. Higher levels of cognitive Engagement and revision effort were also observed among students interacting with AI-generated feedback. Qualitative evidence further indicated that students perceived AI feedback as clear, immediate, and supportive for independent revision. These patterns indicate that AI-generated personalized feedback can serve as a pedagogical scaffold, encouraging reflective revision practices and greater learner Engagement in EFL writing classrooms. The study highlights the potential of AI-assisted feedback as a complementary tool that enhances both the process and outcomes of second language writing development.