Generative AI and L2 Written Feedback Studies: A Scoping Review

Abstract

Since ChatGPT's emergence, extensive research has explored the role of generative artificial intelligence (GenAI) in delivering written feedback (WF), encompassing diverse aims, methodologies and findings. This includes studies examining second language (L2) contexts in which such feedback is used, although, to date, no attempt has been made to synthesize these studies for cumulative knowledge building. To provide clarity on the state-of-the-art on GenAI-influenced L2 WF studies, this Preferred Reporting Items for Systematic Reviews and Meta-Analyses-informed scoping review article explores a dataset of 51 such studies taken from Social Sciences Citation Index/Emerging Sources Citation Index-indexed publications since 2022. Two researchers manually coded these studies for data regarding publication outlets, country/region and L2 focus, research aims, research methods, findings and identified (or author-disclosed) limitations. Findings reveal that most studies address improvements to writing quality arising from GenAI produced feedback, and/or student and teachers’ perceptions of such feedback. A diverse set of methods include revision analysis, pre-tests/post-tests of writing quality and quantitative surveys. Results cover improvements in writing quality or skills, mixed perceptions, and varied feedback uptake and revision behaviours particularly when comparing artificial intelligence and human feedback. We close by identifying gaps in cumulative knowledge and suggesting directions for future research.

The authors' abstract, as published at the source. RELC Journal, 2025 · DOI ↗