Investigating the Relationship between ChatGPT and Writing Strategies
Authors
Institute for Biodiversity and Sustainable Development (IBSD)|1Governance and Policy Studies (GaPS)|Institute of Big Data Analytics and Artificial Intelligence (IBDAAI)|Faculty of Administrative Science and Policy Studies, Universiti Teknologi MARA, Shah Alam (Malaysia)
Competition Law and Consumer Welfare Research Group Interest (RIG), Faculty of Law, Universiti Teknologi MARA, Shah Alam, Malaysia|Faculty of Administrative Science and Policy Studies, Universiti Teknologi MARA, Shah Alam (Malaysia)
Faculty of Administrative Science and Policy Studies, Universiti Teknologi MARA, Shah Alam (Malaysia)
Universiti Tunku Abdul Rahman (UTAR), Kampar, Perak (Malaysia)
Akademi Pengajian Bahasa, Universiti Teknologi MARA, Shah Alam (Malaysia)
Universitas Subang, Indonesia (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100900198
Subject Category: ChatGPT
Volume/Issue: 10/9 | Page No: 2759-2773
Publication Timeline
Submitted: 2026-09-14
Accepted: 2026-09-19
Published: 2026-10-06
Abstract
Generative artificial intelligence (AI) tools such as ChatGPT provide immediate support for academic writing. However, concerns remain about whether students become dependent on AI rather than actively engaging in the writing process. Previous studies have examined technology adoption and academic writing strategies separately, leaving a gap in understanding how students’ perceptions of ChatGPT affect their active writing strategies. Therefore, this quantitative study examined students’ perceptions of ChatGPT. The study was guided by the Technology Acceptance Model (Davis, 1986) and the Cognitive Process Theory of Writing (Flower & Hayes, 1981). Data was collected from 222 participants using questionnaires. Descriptive statistics and correlational analysis were used to examine students’ perceptions and the relationship between ChatGPT use and writing strategies. The findings indicate that students’ acceptance and use of ChatGPT can coexist with active engagement in self-regulated writing processes. The study highlights the importance of using ChatGPT as an interactive learning support rather than a shortcut. Higher education institutions should guide students in using AI effectively while strengthening their metacognitive, cognitive, and effort-regulation writing strategies.
Keywords
ChatGPT, Writing Strategies, Generative tool, Active Engagement
Downloads
References
1. Ahmad, N., Alias, F.A., Hamat, M., & Mohamed, S.A. (2024). Reliability Analysis: Application ofCronbach’s Alpha in Research Instruments. SIG: e-L earning@CS, 114-119.https://appspenang.uitm.edu.my/sigcs/ [Google Scholar] [Crossref]
2. Davis, F.D. (1986) A Technology Acceptance Model for Empirically Testing NewEnd-UserInformation Systems: Theory and Results. Sloan School of Management,Massachusetts Institute of Technology. [Google Scholar] [Crossref]
3. Flower, L., & Hayes, J. R. (1981). A Cognitive Process Theory of Writing. College Composition andCommunication, 32(3), 365-387. [Google Scholar] [Crossref]
4. He, L. (2024) The Application of SPSS Correlation Analysis in the Study if Precision Teaching ofEnglish in Universities. Applied Mathematics and Nonlinear Science, 9(1), 1-13.http://dx.doi.org/10.2478/amns-2024-1371 [Google Scholar] [Crossref]
5. Abdul Rahim, M. A., Zainuddin, A., Aziz, F. M. M., Shazilli, M. S. M., Nizam, S. N. S., & Rahmat, N. H. (2023). Perceived use of online reading strategies online reading problems: A study of relationships between reading strategies. International Journal of Academic Research in Business and Social Sciences, 13(7), 234–252. [Google Scholar] [Crossref]
6. Abdul Rahim, M. A., Zainuddin, A., Soh, M. C., Aziz, F. M. M., Sharif, N. S. I. M., & Rahmat, N. H. (2021). Exploring learning through cognitive constructivism: The case for online lessons. International Journal of Academic Research in Business and Social Sciences, 11(12), 1859–1873. [Google Scholar] [Crossref]
7. Abdul Rahim, M. A., Zainuddin, A., Soh, M. C., Kamal, A. M., Razak, S. A., & Rahmat, N. H. (2023). Exploring motivation to learn online through McClelland’s theory. International Journal of Academic Research in Business and Social Sciences, 13(2), 602–621. [Google Scholar] [Crossref]
8. Rahmat, N.H., Khairruddin, Z., Aripin, N. & Mokhtar, M.I. (2026) Scaffolding Academic WritingUsing AI Assistance: A Systematic Literature Review. International Journal of Research andInnovation in Social Science (IJRISS), 10(1), 7263-7280. https://doi.org/10.47772/IJRISS.2026.10100560 [Google Scholar] [Crossref]
9. Raoofi,S. Miri, A., Gharibi,J. & Malaki, B. (2017). Assessing and Validating a Writing StrategyScale for Undergraduate Students. Journal of Language Teaching and Research, Vol 8(3), pp624-633. http://www.academypublication.com/issues2/jltr/vol08/03/23 [Google Scholar] [Crossref]
10. Vetter, T.R. (2017) Descriptive Statistics: Reporting the Answers to the 5 Basic Questions of Who,What, Why, When , Where, and a Sixth, so What? Anesth Analg, 12595), 1797-1802.https://doi.org/10.1213/ane.0000000000002471 [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]
12. Ziegenfuss, J. Y., Casey A. E., Jennifer M. D., Meghan M. J., Thomas E. K, and Marna, C.. (2021)Impact of Demographic Survey Questions on Response Rate and Measurement: A RandomizedExperiment. Survey Practice 14 (1), https://doi.org/10.29115/SP-2021-0010. [Google Scholar] [Crossref]