By Yeong-Ju Lee, Rauno Parrila, and Danielle Colenbrander
Yeong-Ju Lee: Australian Centre for the Advancement of Literacy, Australian Catholic University, Australia
Rauno Parrila: Australian Centre for the Advancement of Literacy, Australian Catholic University, Australia
Danielle Colenbrander: Australian Centre for the Advancement of Literacy, Australian Catholic University, Australia
Abstract
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.
Keywords: Artificial intelligence, academic writing, task-based language teaching, scaffolding, student-AI interaction, AI-interaction logs
Suggested Citation:
Lee, Y.-J., Parrila, R., & Colenbrander, D. (2026). Adopt, adapt, or reject? Analysing student-AI interaction in university curriculum-aligned writing tasks. Applied Language Sciences, 2, 260102. https://doi.org/10.65553/ALS.260102
Author Biographies
Dr Yeong-Ju Lee obtained her PhD from the Department of Linguistics at Macquarie University. She teaches courses in Applied Linguistics, Language Education, and Literacy. Her research interests include digital language learning and teaching, focusing on digital literacy, multimodality, social media, digital games, and AI. She is the Chief Investigator of the Teaching Development Grant-funded project on AI and literacy at Australian Catholic University, and the Data Horizon Research Centre-funded project on AI and language learning at Macquarie University.
ORCID: 0000-0002-9251-6535
Email: yeong-ju.lee@acu.edu.au & yeong-ju.lee@mq.edu.au
Prof Rauno Parrila is a Professor and the Centre Director of Australian Centre for the Advancement of Literacy. His research focuses on psychological, linguistic, and social correlates of both typical and atypical development of reading and academic achievement. He has a keen interest in reading instruction and interventions, reading development and difficulties in different orthographies, and compensation of learning difficulties in both children and adults.
ORCID: 0000-0003-4250-8980
Email: rauno.parrila@acu.edu.au
Dr Danielle Colenbrander is a Lecturer in the Australian Centre for the Advancement of Literacy. She teaches undergraduate and postgraduate initial teacher education courses in language and literacy. Her research investigates word reading, spelling, and reading comprehension assessment and instruction, with a particular focus on the roles of vocabulary and morphology. With a keen interest in translating research into practice, she has worked closely with teachers and teaching assistants across Australia and the UK.
ORCID: 0000-0001-5577-7501
Email: danielle.colenbrander@acu.edu.au
