AI-assisted academic writing in medical postgraduate education: a cross-sectional study of L2 challenges, affective barriers, and instructional implications

Abstract

Second language (L2) academic writing has become increasingly critical for postgraduate students in non-English speaking contexts, particularly in specialized disciplines such as medicine. However, medical postgraduates often struggle with linguistic challenges, emotional barriers, and limited instructional support. With the rise of AI-based writing tools such as ChatGPT and Grammarly, new opportunities have emerged for supporting these learners—but concerns remain regarding cognitive dependence, ethical boundaries, and pedagogical integration. This study investigates the L2 academic writing experiences of 304 medical postgraduates in China, focusing on writing difficulties, emotional responses, feedback from supervisors, and the use of AI-assisted tools. Using a cross-sectional survey design, we analyzed students’ self-reported abilities, affective states, and writing behaviors. Results revealed that while most students had prior experience in English writing, they reported persistent challenges with discourse organization, tone control, and academic style. Writing anxiety, procrastination, and lack of emotional regulation were common. Supervisor feedback was seen as valuable but inconsistently delivered. AI tools such as ChatGPT and Grammarly were widely used for grammar correction and polishing, and generally perceived as helpful, though concerns about over-reliance emerged. Findings highlight the need for a comprehensive pedagogical framework that integrates L2 writing instruction, affective support, and ethical use of AI to empower domain-specific postgraduate learners.

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