Beyond detection: GenAI in EAL writing education

This study investigates how generative artificial intelligence (GenAI) shapes the writing practices of five Chinese English as an additional language (EAL) students and how emerging GenAI-text detection practices mediate that use. Findings from screen-recordings, written drafts, and interviews reveal four recurrent functions of GenAI use, that is, brainstorming, structuring, occasional drafting, and revising, yet students calibrated their reliance on each function against the perceived risk of being flagged by GenAI detectors. To mitigate that risk, participants shuttled between ChatGPT, Grammarly, and self-paraphrase to ‘humanise’ GenAI output, occasionally reallocating effort from idea development to surface revision. The study, therefore, problematises a detection-first approach, showing that it (1) engenders strategic but pedagogically hollow text manipulation, (2) complicates ‘plagiarised’ versus ‘original’ writing, and (3) potentially shifts assessment towards product-centric criteria. The study argues for cultivating critical AI literacy so that GenAI-assisted EAL writing instruction can prioritize creativity, voice, and argument quality over algorithmic policing.

Duke Scholars

Author Yachao Sun DKU Faculty