Effects of AI-Driven Written Direct and Indirect Feedback on Iranian Intermediate EFL Learners' Writing Complexity

Articles in Press

Document Type : Research Paper

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Department of English, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran

Abstract

This study examined the impact of AI-driven feedback on the writing complexity of Iranian intermediate EFL learners using a quasi-experimental design. Through convenience sampling, 100 participants (male and female, aged 18-25) from two language institutes in Tehran were divided into four groups: two experimental groups receiving direct and indirect feedback from AI ChatGPT, and two control groups receiving the same feedback types from their teacher. Participants completed a pre-test, ten writing tasks over 14 weeks, and a post-test. Results, analyzed via descriptive statistics and one-way ANOVA, indicated notable improvements in writing complexity across all groups. The AI direct feedback group showed the highest improvement, with a mean difference of 5.24 (p < 0.05), followed by the teacher direct feedback group, which also demonstrated significant gains. The AI indirect feedback group exhibited moderate progress, while the teacher indirect feedback group showed the least improvement. Analysis of syntactic measures revealed that AI feedback, particularly direct feedback, effectively enhanced sentence structures and encouraged the use of more sophisticated vocabulary. These findings highlight AI-driven feedback’s potential to enhance EFL learners’ writing complexity, with direct feedback yielding the greatest benefits.

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Journal of English Language Teaching and Learning

Articles in Press, Accepted Manuscript
Available Online from 30 April 2025

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