Comparing Teacher Written Corrective Feedback and AI-Generated Feedback in EFL Writing Classrooms
Abstract
This study examines the comparative effectiveness of teacher written corrective feedback (WCF) and AI-generated feedback in English as a Foreign Language (EFL) writing classrooms. Written corrective feedback plays a crucial role in improving learners’ writing accuracy, grammatical competence, and revision strategies. With the rapid integration of artificial intelligence (AI) tools such as ChatGPT and Grammarly in language education, it has become essential to evaluate their pedagogical value in comparison with traditional teacher feedback. This research adopts a mixed-methods approach involving undergraduate EFL students at a university level. Quantitative data are collected through pre-tests and post-tests of students’ writing performance, while qualitative data are gathered through student questionnaires and semi-structured interviews to explore perceptions of both feedback types. The study compares the impact of teacher feedback and AI-generated feedback on grammatical accuracy, lexical choice, coherence, and overall writing quality. Findings are expected to reveal that teacher feedback provides deeper contextual and personalized guidance, whereas AI-generated feedback offers immediate, accessible, and consistent support for revision. The study also explores students’ preferences, trust, and attitudes toward using AI tools for academic writing improvement. The research contributes to current discussions on technology-enhanced language learning by identifying the strengths and limitations of both feedback approaches. It offers practical implications for integrating AI responsibly into EFL writing pedagogy while maintaining the essential role of teachers in developing students’ academic writing skills.
Keywords: Written Corrective Feedback, Artificial Intelligence, AI-Generated Feedback, EFL Writing, Teacher Feedback, ChatGPT, Grammarly, Academic Writing
