The Shared Scaffold: A Metacognitive Framework of AI’s Influence on Self-Regulated Writing
Authors
Universiti Teknologi MARA Perak Branch Seri Iskandar Campus (Malaysia)
Universiti Teknologi MARA Shah Alam (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.102100088
Subject Category: Education
Volume/Issue: 10/21 | Page No: 1038-1047
Publication Timeline
Submitted: 2026-07-09
Accepted: 2026-07-14
Published: 2026-07-25
Abstract
The integration of Artificial Intelligence (AI) tools such as ChatGPT and writing needs systematic self-regulation to encourage authentic learning despite transforming the writing process in the fast-changing field of digital pedagogy. Although current studies have extensively documented AI capabilities, there is a theoretical gap in our knowledge of how learners systematically regulate their cognition and behaviour when working with generative AI. This conceptual paper proposes an integrated model of Pintrich Self-Regulated Learning (SRL) and Raoofi et al. taxonomy of L2 writing strategies. The framework maps four phases of regulation, forethought, monitoring, control and reflection, against specific cognitive and metacognitive writing strategies adapted to AI environments that describes how learners can design prompts intentionally, check the accuracy of AI-generated responses, guide the path of their writing, and think about their revised writings. Ultimately, the framework offers a theory-based template for AI transforming change from a shortcut into a cognitive scaffold. This paper foregrounds active learner agency as a priority, rather than passive dependence on AI, and provides educators and researchers with a framework for promoting critical thinking, maximizing writing performance, and supporting autonomous and digitally mediated literacy learning in higher education.
Keywords
self-regulated learning, writing strategies, AI
Downloads
References
1. Almudara, S. B., Alshehri, O. A., Alzahrani, S. Y., Abdellatif, M. S., Idris, A. I., & Ibrahim, A. R. (2026). Working memory and generative AI tools in higher education: A systematic review. Research Journal in Advanced Humanities, 7(2). https://doi.org/10.58256/ca66cf85 [Google Scholar] [Crossref]
2. Chen, J., & Alibakshi, G. (2026). AI-Powered Applications’ Effects on English Language Learners’ Cognitive, Metacognitive, and Resource Management Strategies, and Language Achievement. Journal of Computer Assisted Learning, 42(1), e70171. https://doi.org/10.1002/jcal.70171 [Google Scholar] [Crossref]
3. Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., Soomro, R. B. (2024). Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study. Heliyon, 10(8), e29317. https://doi.org/10.1016/j.heliyon.2024.e29317 [Google Scholar] [Crossref]
4. Hauske, S., & Bendel, O. (2024). How Can GenAI Foster Well-being in Self-regulated Learning? Proceedings of the AAAI Symposium Series [Google Scholar] [Crossref]
5. Khairuddin, Z., Rahmat, N.H., Noor, M.M., & Khairuddin, Z. (2021) The Use of Rhetorical Strategies in Argumentative Essays. Pertanika Journal of Social Sciences & Humanities, 29(S3), 263-285). https://doi.org/10.47836/pjssh.29.S3.14 [Google Scholar] [Crossref]
6. Pintrich, P. R. (2002). The Role of Metacognitive Knowledge in Learning, Teaching, and Assessing. Theory into Practice, 41, 219-225. https://doi.org/10.1207/s15430421tip4104_3 [Google Scholar] [Crossref]
7. Rahmat, N. H. (2021) An Investigative Study of Cognitive and Metacognitive Paraphrasing Strategies in ESL Writing. International Journal of Academic Research in Business & Social Sciences, 11(3), 76-87. http://dx.doi.org/10.6007/IJARBSS/v11-i3/8919 [Google Scholar] [Crossref]
8. Lai, J. W. (2024). Adapting Self-Regulated Learning in an Age of Generative Artificial Intelligence Chatbots. Future Internet, 16(6), 218. https://doi.org/10.3390/fi16060218 [Google Scholar] [Crossref]
9. Li, X. J., Wang, T., Wang, W., & Liu, L. (2026). Fostering engagement in the digital age: The mediating role of self-efficacy and self-regulation between enjoyment and learner engagement in AI-assisted EFL writing. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1848701 [Google Scholar] [Crossref]
10. Raoofi, S., Miri, A., Gharibi, J. & Malaki, B. (2017) Assessing and Validating a Writing Strategy Scale for Undergraduate Students. Journal of Language Teaching and Research, Vol 8(3), pp 624-633. Retrieved from http://www.academypublication.com/issues2/jltr/vol08/03/23.pdf [Google Scholar] [Crossref]
11. Youssef, E., Medhat, M., Abdellatif, S., & Al Malek, M. (2024) Examining the effect of ChatGPT usage on students’ academic learning and achievement: A survey-based study in Ajman, UAE. Computers and Education: Artificial Intelligence, 7(Dec 2024), 100316. https://doi.org/10.1016/j.caeai.2024.100316 [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
- Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
- “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
- Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
- Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study