Artificial Intelligence in Learning and Legal Writing: Examining the Relationship Between Perceived Usefulness and Writing Anxiety
Authors
Academy of Language Studies, Universiti Teknologi MARA, Melaka (Malaysia)
Law Faculty, Universiti Teknologi MARA, Melaka (Malaysia)
Academy of Language Studies, Universiti Teknologi MARA, Melaka (Malaysia)
Academy of Language Studies, Universiti Teknologi MARA, Melaka (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100400140
Subject Category: Language
Volume/Issue: 10/4 | Page No: 1879-1891
Publication Timeline
Submitted: 2026-04-08
Accepted: 2026-04-13
Published: 2026-04-30
Abstract
The use of Artificial Intelligence (AI) tools at the tertiary level has transformed the way learners approach academic writing particularly in the context of discipline-specific settings in English-medium contexts. This study investigates 60 non-law students’ perceptions of using AI tools to support their learning of law subjects and legal writing abilities, and how this relates to writing anxiety. This study also examines the learners’ views about ethical considerations when using AI tools in their studies. Employing a mixed-methods approach, data were collected using a structured questionnaire comprising an adapted version of the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Second Language Writing Anxiety Inventory (SLWAI), including open-ended responses. Quantitative data were analysed using descriptive statistics, correlation and regression analysis, while qualitative data were examined thematically. The findings indicate that students generally have a positive perception about the usefulness of technology, particularly in enhancing their understanding and building the language skills required in legal writing. A negative relationship was also found between perceived usefulness of AI tools and writing anxiety, indicating that higher perceptions of AI usefulness result in lower levels of writing anxiety. Regarding ethical considerations, students reported feeling anxious when utilising AI tools due to fear of over reliance. The findings indicate that the integration and utilisation of AI tools in legal contexts require clear and ethical principles to provide students with the cognitive scaffolding required to support both the cognitive and emotional aspects of students’ learning.
Keywords
Artificial Intelligence, Legal Writing
Downloads
References
1. Alamri, M. (2024). Artificial intelligence adoption in higher education: Applying the unified theory of acceptance and use of technology. Education and Information Technologies, 29, 10231–10250. https://doi.org/10.1007/s10639-023-12190-3 [Google Scholar] [Crossref]
2. Andreou, G., & Christani, P. (2025). The benefits and limitations of the use of generative artificial intelligence tools in the acquisition of productive skills in English as a foreign language—A systematic analysis. Applied Sciences, 15(21), 11476. https://doi.org/10.3390/app152111476 [Google Scholar] [Crossref]
3. Abubakar, S., Jeilani, A., & Yusuf, M. (2025). The role of over-reliance on AI in the negative consequences of student learning: The moderating effects of ethical concerns and institutional policies. Cogent Education. https://doi.org/10.1080/2331186X.2025.2591503 [Google Scholar] [Crossref]
4. Bearman, M., & Ajjawi, R. (2023). AI and assessment in higher education: Rethinking academic integrity. Assessment & Evaluation in Higher Education, 48(7), 1025–1037. https://doi.org/10.1080/02602938.2023.2170979 [Google Scholar] [Crossref]
5. Bhatia, V. K. (1993). Analysing genre: Language use in professional settings. Longman. [Google Scholar] [Crossref]
6. Cheng, Y. S. (2002). Factors associated with foreign language writing anxiety. Foreign Language Annals, 35(6), 647–656. https://doi.org/10.1111/j.1944-9720.2002.tb01903.x [Google Scholar] [Crossref]
7. Chiu, T. K. F. (2023). Student use of generative artificial intelligence in higher education. Educational Technology Research and Development, 71, 2345–2364. https://doi.org/10.1007/s11423-023-10291-8 [Google Scholar] [Crossref]
8. Cotton, D., Cotton, P., & Shipway, R. (2024). ChatGPT: Implications for teaching and learning in higher education. Innovations in Education and Teaching International, 61(2), 256–268. https://doi.org/10.1080/14703297.2023.2195843 [Google Scholar] [Crossref]
9. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage. [Google Scholar] [Crossref]
10. Granström, M., & Oppi, P. (2025). Student engagement with AI tools in learning: Evidence from a large-scale Estonian survey. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1688092 [Google Scholar] [Crossref]
11. Harefa, J. T. V., Manik, K. A., Habehan, Z. L., Juniarta, & Cicilia, S. L. (2025). Stress, anxiety, depression and social media in Generation Z: A scoping review. Mental Health Chronicle, 4(3). https://doi.org/10.56922/mhc.v4i3.1362 [Google Scholar] [Crossref]
12. Hyland, K. (2023). Disciplinary discourses: Social interactions in academic writing (3rd ed.). Routledge. [Google Scholar] [Crossref]
13. Kasneci, E., et al. (2023). ChatGPTfor good? Opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274 [Google Scholar] [Crossref]
14. Khairuddin, Z., Shahabani, N. S., Ahmad, S. N., Ahmad, A. R., & Zamri, N. A. (2024). Students’ perceptions on the artificial intelligence (AI) tools as academic support. Malaysian Journal of Social Sciences and Humanities, 9(11). https://doi.org/10.47405/mjssh.v9i11.3087 [Google Scholar] [Crossref]
15. Klimova, B., & Pikhart, M. (2025). Exploring the effects of artificial intelligence on student and academic well-being in higher education: A mini-review. Frontiers in Psychology, 16, 1498132. https://doi.org/10.3389/fpsyg.2025.1498132 [Google Scholar] [Crossref]
16. Lee, J., & Kim, H. (2023). Writing anxiety among ESL learners in English-medium instruction environments. Journal of Language Teaching and Research, 14(2), 412–420. https://doi.org/10.17507/jltr.1402.13 [Google Scholar] [Crossref]
17. Nazari, M., Shabbir, M., & Setiawan, R. (2024). Artificial intelligence-assisted academic writing and language learning. Computer Assisted Language Learning, 37(3), 501–520. https://doi.org/10.1080/09588221.2023.2177655 [Google Scholar] [Crossref]
18. Park, E. G., Lim, S., & Cho, M. H. (2026). College students’ intention to use AI tools in academia. International Journal of Emerging Technologies in Learning, 21(1), 43–58. https://doi.org/10.3991/ijet.v21i01.58065 [Google Scholar] [Crossref]
19. Pajares, F., Johnson, M. J., & Usher, E. L. (2006). Sources of writing self-efficacy beliefs of elementary, middle, and high school students. Research in the Teaching of English, 41(1), 104–120. [Google Scholar] [Crossref]
20. Rahmat, N. H., & Rahman, S. A. (2024). Writing anxiety among university ESL learners. International Journal of Education and Literacy Studies, 12(1), 45–53. [Google Scholar] [Crossref]
21. Reyes, M., Merculio, R., & Ravago, M. (2024). Writing anxiety and academic performance among university students. Asian Journal of Education, 5(2), 88–101. [Google Scholar] [Crossref]
22. Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT and academic integrity in higher education. Journal of Applied Learning and Teaching, 6(1), 1–22. [Google Scholar] [Crossref]
23. Shrestha, N. K. (2025). Students’ ethical awareness and behavior intentions in the use of AI tools. BIC Journal of Management, 2(1), 93–108. [Google Scholar] [Crossref]
24. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. [Google Scholar] [Crossref]
25. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology. MIS Quarterly, 36(1), 157–178. [Google Scholar] [Crossref]
26. Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2024.124167 [Google Scholar] [Crossref]
27. Wächter, B., & Maiworm, F. (2022). English-taught programmes in European higher education: The state of play. Academic Cooperation Association (ACA) papers [Google Scholar] [Crossref]
28. Wen, F., Li, Y., Zhou, Y., An, X., & Zou, Q. (2024). A study on the relationship between AI anxiety and AI behavioral intention of secondary school students learning English as a foreign language. Journal of Educational Technology Development and Exchange, 17(1), 130–154. https://doi.org/10.18785/jetde.1701.07 [Google Scholar] [Crossref]
29. Zawacki-Richter, O., Bond, M., Marin, V., & Gouverneur, F. (2024). Artificial intelligence in higher education: A systematic review. International Journal of Educational Technology in Higher Education, 21(5). https://doi.org/10.1186/s41239-024-00410-5 [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Evaluating the Impacts of Mind Mapping Strategy on Developing EFL Students’ Critical Reading Skills
- Significance of Reading Instructions for Language Improvement in Children with Down Syndrome
- Prenasalised Consonants in Liangmai
- Metadiscourse Matters: Definitions, Models, and Advantages for ESL/ EFL Writing
- Blank Minds and Stuck Voices: Understanding and Addressing Cognitive Anxiety in High-Stakes ESL Speaking Tests