A Comparative Study of the Effect of AI-Scaffolded Vs. Teacher-Scaffolded Corrective Feedback: Writing Performance and Learner Attitudes

In the field of EFL education, providing effective CF (CF) is essential for improving writing skills. This study explores how AI-scaffolded CF compares to traditional feedback from teachers in enhancing writing performance among learners. Despite the increasing integration of technology in language learning, there is a surprising lack of research directly comparing these two feedback types. A quasi-experimental study was conducted with a convenience sample of 60 advanced EFL learners, randomly placed into two groups: one receiving feedback from instructors and the other using the Sider AI writing tool. Later, the participants completed a writing pre-test and a post-test to assess changes in their writing accuracy. The results revealed significant improvements in both groups, but those using AI-enhanced feedback demonstrated more substantial gains in writing performance. Paired and independent samples t-tests revealed that while both groups improved significantly, the AI-scaffolded group achieved statistically higher post-test scores than the teacher-scaffolded group. Survey results showed that while AI tools effectively engaged learners through personalized comments, the emotional and collaborative support from teachers was invaluable. This study suggests a blended approach that combines AI and teacher feedback to better meet the varied needs of learners. The findings underscore the importance of AI in EFL instruction and highlight the need for further exploration of hybrid feedback strategies and their long-term effects on writing outcomes.