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Perspective Article
AI-Mediated Written Corrective Feedback in L2 Writing: What Changes, What Doesn’t, and What We Still Don’t Know
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This reflective commentary revisits key insights from research on written corrective feedback (WCF) within the context of feedback facilitated by large language models (LLMs) in higher-education L2 writing. The CAF framework shows that accuracy is most consistently improved through targeted, well-designed feedback. In contrast, claims about complexity and fluency should be approached cautiously, as they depend on factors like task design, sequencing, and learner engagement. The paper distinguishes between traditional automated writing assessments and the generative, dialogic features of LLMs. It proposes a straightforward approach for teachers to provide feedback, including specific prompts, metalinguistic explanations, learner reformulation, genre confirmation, and reflection periods. The paper emphasises that the educational value of LLM-based WCF relies more on thoughtful mediation, ethical considerations, and alignment with assessment goals than on speed or novelty. It concludes by highlighting priority areas for future research, such as the durability of learning gains, transfer from assisted to independent writing, the interaction of dose, timing, and scope, maintaining learner engagement, and ensuring equitable access to AI-mediated feedback across proficiency levels.
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Keywords
Written Corrective Feedback; Large Language Models (LLMs); Complexity-Accuracy-Fluency (CAF); Feedback Literacy; Second-Language Writing; Assessment Integrity
Author(s) Information
Publisher’s Note
The claims, arguments, and counter-arguments made in this article are exclusively those of the contributing authors. Hence, they do not necessarily represent the viewpoints of the authors’ affiliated institutions, or EUROKD as the publisher, the editors and the reviewers of the article.
Acknowledgements
We would like to thank the editors for their comments and support.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
CRediT Authorship Contribution Statement
Konstantinos M. Pitychoutis: Conceptualisation, Methodology, Writing Original Draft, Review & Editing, Supervision
Filomachi Spathopoulou: Conceptualisation, Writing Original Draft, Review & Editing
Generative AI Use Disclosure Statement
The authors used Grammarly Premium for proofreading and editing this manuscript. All substantive intellectual content, argumentation, and conclusions are the authors’ own. The authors take full responsibility for the accuracy and integrity of the published work.
Ethics Declarations
World Medical Association (WMA) Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Participants
This paper is a reflective theoretical commentary involving no primary research with human participants. The Declaration of Helsinki is therefore not applicable.
Competing Interests
The authors declare no competing interests.
Data Availability
No primary data were generated or analysed in the preparation of this manuscript.