• Generative AI can help multilingual communicators in professional writing. • Generative AI supports email/report writing and meeting summary. • Practical, ethical and legal concerns remain. • Students’ AI use at workplace informs academic writing teaching and learning. Because multilingual students’ languaging practices are not limited to academic settings, it is important to explore their lived experiences communicating in real-world situations to shed light on how to prepare them in college classrooms in the era of generative AI. Drawing upon writing samples, artifacts and interview data, this case study brings attention to the potential and challenges a multilingual international student face in implementing generative AI-assisted written communication during her 5-month internship in the workplace. The findings indicate that generative AI tools, especially ChatGPT, have the potential to help multilingual communicators meet their written linguistic demands in professional contexts, especially in email writing, report drafting and meeting summary. Generative AI-assisted writing tools could assist multilingual students with idea expression and boost their confidence and agency in communication. Yet, despite its many advantages, practical, ethical and legal concerns remain. This study contributes to the scarce yet budding literature exploring multilingual international students’ AI engagement in professional settings and offers concrete pedagogical implications and directions for future research.

• Postgraduates engaged behaviorally, affectively, and cognitively with GenAI feedback. • Postgraduates dealt with ChatGPT primarily as a tool for refining their proposals, not for generating content. • Postgraduates demonstrated agency by actively questioning, annotating, and negotiating feedback. • Postgraduates engaged in diverse affective responses, ranging from appreciation to frustration. As Generative artificial intelligence (GenAI) tools such as ChatGPT are becoming increasingly integrated into English as a Foreign Language (EFL) academic writing context, learners’ engagement with AI-generated feedback remains insufficiently examined. This case study investigated how four Chinese EFL postgraduates joining a course in a Malaysian university engaged with ChatGPT feedback while revising their academic research proposals. The study triangulated screen recordings, pre- and post-revision drafts, and stimulated recall interviews. Participants displayed a range of behavioural strategies, including accepting, questioning, rejecting suggestions, annotating visually, and seeking external validation. Affective responses ranged from appreciation and curiosity to doubt and frustration, particularly when feedback appeared conflicting or imprecise. Cognitively, learners applied various strategies such as evaluating, comparing, negotiating feedback, and regulating its use. Yet, they showed differing levels of engagement, shaped by individual perceptions and writing intentions. Importantly, participants regarded ChatGPT as a tool for linguistic refinement rather than content generation. Overall, the findings revealed that learners did not passively receive feedback but interacted with it in agentive and critical ways. The study highlights the interplay among these three dimensions of engagement and the importance of individual differences when evaluating the pedagogical potential of GenAI-generated feedback in academic writing.

This case study investigates how two ESL graduate students, Ian and Sam, use ChatGPT in their research writing after receiving a comprehensive tutorial based on Warschauer et al.’s (2023) AI literacy framework. We analyzed their engagement with ChatGPT across prompt categories including genre, content, language use, documentation, coherence, and clarity. Data were collected from research paper drafts, ChatGPT chat histories, and interviews. Data analyses included coding ChatGPT prompts, textual analysis of drafts, and thematic analysis of interview transcripts . Results show that while both participants utilized ChatGPT for understanding genre conventions and content development, they developed distinct approaches reflecting their individual backgrounds. Ian selectively used ChatGPT for specific assistance needs, while Sam engaged more systematically, particularly for APA style and coherence checks. Both approaches maintained academic integrity and scholarly voice, demonstrating that Generative AI tools can be effectively tailored to individual needs without compromising ethical standards. This study highlights how advanced ESL writers can adapt GenAI tools to their unique writing processes, offering insights into the diverse ways AI can enhance academic writing while preserving individual agency. The findings suggest that AI integration in academic writing can be customized to support diverse writing goals and backgrounds.

• This study explores GenAI's role in multimodal composition, including Adobe Firefly and DALL·E. • GenAI reshapes the composition stages of invention, designing, and revising. • Despite its limitations, GenAI offers alternative solutions to wicked problems. • Post-GenAI use, students critically revise and iterate their compositions. • The study contributes to future research and teaching of AI-assisted composition. This study explores the integration of generative artificial intelligence (GenAI) design technologies, including Adobe Firefly and DALL·E, into the teaching and learning of multimodal composition. Through focus group discussions and case studies, this paper demonstrates the potential of GenAI in reshaping the various stages of the composition process, including invention, designing, and revising. The findings reveal that GenAI technologies have the potential to enhance students’ multimodal composition practices and offer alternative solutions to the wicked problems encountered during the design process. Specifically, GenAI facilitates invention by offering design inspirations and enriches designing by expanding, removing, and editing the student-produced design contents. The students in this study also shared their critical stance on the revision process by modifying and iterating their designs after their uses of GenAI. Through showcasing both the opportunities and challenges of GenAI technologies, this paper contributes to the ongoing scholarly conversations on multimodal composition and pedagogy. Moreover, the paper offers implications for the future research and teaching of GenAI-assisted multimodal composition projects, with the aim of encouraging thoughtful integration of GenAI technologies to foster critical AI literacy among college composition students.