Adopt, adapt, or reject? Analysing student-AI interaction in university curriculum-aligned writing tasks

Artificial intelligence (AI) is reshaping academic writing instruction. However, there is limited evidence on how students actually interact with AI and how pedagogy can guide ethical and reflective engagement. Piloted in a first-year undergraduate English language and literacy unit at an Australian university, this paper presents the design and trial of curriculum-aligned, task-based writing materials comprising an AI-assisted guide with structured prompts to support essay preparation with AI. Analysis draws on AI-interaction logs from a case study, complemented by a survey of 207 students. Thematic coding and interactional move analysis of AI-interaction logs observed four recurrent moves – clarification, uptake, adaptation, and rejection – in which the learner negotiated AI feedback. Survey data indicated that while students viewed AI as useful for efficiency and confidence, concerns about plagiarism and over-reliance persisted. This study offers early insights into how structured scaffolds can support ethical, reflective engagement with AI and inform future research.