The Combined Impact of ChatGPT and Teacher Feedback on the Syntactic Complexity of EFL Learners’ Writing

This study explores the use of artificial intelligence (AI) in language learning, focusing on its ability to enhance English as a Foreign Language (EFL) writing. Specifically, it examines the effect of integrating ChatGPT feedback with teacher feedback on the syntactic complexity of Saudi EFL learners’ writing. A quasi-experimental design was employed, involving two intact groups of undergraduate students ( n = 35) enrolled in an academic writing course. The 9-week intervention provided the experimental group with integrated ChatGPT and teacher feedback, while the control group received only teacher feedback. Pre- and post-test essays were analyzed using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TAASSC), covering 177 indices across global, clausal, and phrasal levels. Results showed that the combined feedback condition did not produce a reliable advantage over teacher feedback alone at the global or clausal levels of syntactic complexity. At the phrasal level, a limited set of noun phrase–related indices revealed post-test differences between groups, suggesting localized, feature-specific development rather than broad syntactic restructuring within a short instructional period. However, these differences did not remain statistically significant after false discovery rate (FDR) correction and are therefore interpreted as exploratory rather than confirmatory. The findings are discussed in relation to previous research on AI-mediated feedback and FL writing development, and pedagogical as well as research implications for the integration of AI tools in EFL writing instruction are outlined.