Identity, Agency, and Human–AI Mediation in L2 Academic Writing: An Interactional Study

Generative language models are increasingly used in academic writing, yet research on AI-assisted writing often reduces them to instructional tools or feedback providers and relies mainly on outcomes or self-reports. This study instead examines human–AI coordination as the analytic focus and conceptualizes composing as a distributed activity involving writers, prompts, system outputs, and evolving drafts. Drawing on human–computer interaction and distributed cognition, it reports a 12-week longitudinal qualitative study of 25 multilingual L2 academic writers. Data include AI interaction logs, time-stamped draft histories, screen recordings, and stimulated recall interviews anchored in observable interactional moments. Analysis of episodes linking prompts, AI output, writer uptake, and draft change shows that agency emerges through cycles of proposal, evaluation, constraint tightening, and consolidation, while identity is negotiated through selective alignment with AI-generated academic voice and disciplinary norms.