Artificial Intelligence in EFL Writing Enhancement

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.

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Publication Details

Journal
International Journal of Web-Based Learning and Teaching Technologies
Published
2025-10-10
DOI
https://doi.org/10.4018/ijwltt.390442
Primary Topic
Educational Technology and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in EFL Writing Enhancement

Ning Gao, Nan Yang, Tengda Zhang
International Journal of Web-Based Learning and Teaching Technologies
Educational Technology and Pedagogy
article

Artificial Intelligence in EFL Writing Enhancement

Ning Gao, Nan Yang, Tengda Zhang
article en

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.

International Journal of Web-Based Learning and Teaching TechnologiesVol. 20(1)
Baotou Teachers College (CN), Baotou Medical College (CN)
Openalex Percentile: Top 85%
Educational Technology and Pedagogy
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