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Artificial Intelligence in EFL Writing Enhancement: A Study on Chatbot Feedback and Learner Autonomy

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  • Nan Yang

    (Baotou Teacher's College, China)

  • Ning Gao

    (Baotou Medical College, China)

  • Tengda Zhang

    (Baotou Medical College, China)

Abstract

Writing is a challenging aspect of second language acquisition, especially among English as a Foreign Language learners. This paper examines an online AI chatbot application that offers learners context-sensitive feedback on writing tasks, making it a valuable component of scalable online learning environments that promote learner autonomy. A transformer-based NLP system, using essays of the International Corpus of Learner English (ICLE), produced context-based and multi-layered feedback on grammar, vocabulary, and discourse-level characteristics. Changes in lexical diversity (MTLD), syntactic complexity (C/T), and cohesion were measured using a model of a simulated revision task. Findings indicated significant language gains and increased self-reliance among high-level learners through self-directed revisions. The results suggest the potential of chatbots as writing partners in blended and asynchronous learning settings. The following trends are anticipated for the future: classroom testing, provision of assistance to lower-level students, and hybrid AI-teacher feedback systems.

Suggested Citation

  • Nan Yang & Ning Gao & Tengda Zhang, 2025. "Artificial Intelligence in EFL Writing Enhancement: A Study on Chatbot Feedback and Learner Autonomy," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 20(1), pages 1-40, January.
    • Handle: RePEc:igg:jwltt0:v:20:y:2025:i:1:p:1-40
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