INVESTIGATING THE IMPACT OF AI-FEEDBACK VS TEACHER FEEDBACK ON EFL STUDENT'S REVISION PROCESSES IN EXPOSITORY WRITING TASKS
Keywords:
AI-feedback, teacher feedback, EFL students, revision process, expository writingAbstract
This study aims to investigate the impact of artificial intelligence-based feedback compared to teacher feedback on EFL (English as a Foreign Language) students' revision process in expository writing assignments. In the context of English language learning, providing feedback is crucial for helping students improve their writing quality and metacognitive awareness of the writing process. With the advancement of artificial intelligence technology, various digital platforms are now capable of providing rapid and detailed automated feedback, rivaling the effectiveness of traditional teacher feedback. Using a literature review, this study compiled and analyzed the results of previous empirical studies that evaluated the effectiveness, accuracy, and influence of these two forms of feedback on EFL writers' revision strategies. The literature review revealed that AI-feedback has the advantage of providing instant and objective responses that help students efficiently identify linguistic errors, while teacher feedback remains superior in providing contextual guidance, nuanced meaning, and affective support that play a crucial role in shaping student motivation and engagement. Thus, this study highlights the importance of a hybrid approach that integrates AI-feedback with human intervention to create a more effective, personalized, and sustainable revision process in academic writing learning.
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