Approaching the Limits to EFL Writing Enhancement with AI-generated Text and Diverse Learners

David James Woo, Hengky Susanto, Chi Ho Yeung, Kai Guo
3/1/2025
cs.CL

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Abstract

Generative artificial intelligence (AI) chatbots, such as ChatGPT, are reshaping how English as a foreign language (EFL) students write since students can compose texts by integrating their own words with AI-generated text. This study investigated how 59 Hong Kong secondary school students with varying levels of academic achievement interacted with AI-generated text to compose a feature article, exploring whether any interaction patterns benefited the overall quality of the article. Through content analysis, multiple linear regression and cluster analysis, we found the overall number of words -- whether AI- or human-generated -- is the main predictor of writing quality. However, the impact varies by students' competence to write independently, for instance, by using their own words accurately and coherently to compose a text, and to follow specific interaction patterns with AI-generated text. Therefore, although composing texts with human words and AI-generated text may become prevalent in EFL writing classrooms, without educators' careful attention to EFL writing pedagogy and AI literacy, high-achieving students stand to benefit more from using AI-generated text than low-achieving students.

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@article{woo2025approaching,
  title  = {Approaching the Limits to EFL Writing Enhancement with AI-generated Text and Diverse Learners},
  author = {David James Woo and Hengky Susanto and Chi Ho Yeung and Kai Guo},
  year   = {2025},
  eprint = {2503.00367},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.00367v2}
}

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