Generative AI in English Language Education: A PRISMA-Based Systematic Review and Implications for Technical English in Malaysian Polytechnics

Authors

Nurul Fathiha binti Ibrahim

General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)

Suzianah binti Sahar

General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)

Teng Yee Leng

General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)

Diana binti Ahmad Busra

General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.100600547

Subject Category: Education

Volume/Issue: 10/6 | Page No: 7861-7875

Publication Timeline

Submitted: 2026-06-06

Accepted: 2026-06-11

Published: 2026-06-29

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) has created new opportunities for enhancing teaching and learning across educational contexts, including English language education. Tools such as ChatGPT, Gemini, Copilot, and NotebookLM have demonstrated considerable potential in supporting writing development, personalised learning, communication practice, and learner engagement. Despite growing interest in GenAI, limited research has specifically examined its implications for Technical English education within Malaysian Technical and Vocational Education and Training (TVET) institutions, particularly Malaysian Polytechnics. This study aims to synthesise current evidence regarding the applications, benefits, and challenges of GenAI in English language education and explore its potential relevance to Technical English instruction in Malaysian Polytechnics. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) framework, a systematic review was conducted using studies published between 2021 and 2026. Relevant literature was retrieved from Scopus, Web of Science, ERIC, ScienceDirect, and Google Scholar. Following screening and eligibility procedures, 15 studies were included in the final synthesis. The findings revealed five major themes: academic and technical writing enhancement; personalised learning and learner autonomy; communication skills and vocational English development; learner engagement and motivation; and ethical, pedagogical, and institutional challenges. The review highlights the potential of GenAI to support Technical English learning while emphasising the importance of responsible implementation, AI literacy, and institutional preparedness. The findings provide useful insights for educators, curriculum developers, and policymakers seeking to integrate GenAI into Technical English education within Malaysian Polytechnics.

Keywords

Generative Artificial Intelligence, Technical English, Malaysian Polytechnic, TVET, English language education, PRISMA, systematic review

Downloads

References

1. Alpar, M. (2025). Generative artificial intelligence tools in English writing instruction: A comparative analysis of ChatGPT, Gemini, and Copilot. European Journal of Educational Research, 14(4), 1291–1308. https://doi.org/10.12973/eu-jer.14.4.1291 [Google Scholar] [Crossref]

2. Alsaedi, A. (2024). ChatGPT in ESL and EFL writing: Opportunities and challenges. English Language Teaching, 17(5), 41–54. https://doi.org/10.5539/elt.v17n5p41 [Google Scholar] [Crossref]

3. Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Siam, L., Tissenbaum, M., Knight, S., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-023-00436-z [Google Scholar] [Crossref]

4. Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8 [Google Scholar] [Crossref]

5. Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI than their lecturers? Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00269-3 [Google Scholar] [Crossref]

6. Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00392-8 [Google Scholar] [Crossref]

7. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar] [Crossref]

8. Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback and its implications for writing instruction in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00425-2 [Google Scholar] [Crossref]

9. Huang, J., & Yan, Z. (2025). Generative artificial intelligence in English language education: Opportunities, challenges, and future directions. TESOL Quarterly. Advance online publication. https://doi.org/10.1002/tesq.70042 [Google Scholar] [Crossref]

10. Karataş, F., Kalaycı, N., & Yılmaz, M. (2024). Investigating the role of ChatGPT in foreign language learning: Opportunities and challenges. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12574-6 [Google Scholar] [Crossref]

11. Kim, J., Lee, S., & Park, H. (2024). Students’ perceptions of generative AI-assisted academic writing in higher education. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12878-7 [Google Scholar] [Crossref]

12. Kohnke, L., Moorhouse, B. L., & Zou, D. (2025). Generative artificial intelligence for personalised English language learning: A systematic review. Computers and Education: Artificial Intelligence, 8, 100371. https://doi.org/10.1016/j.caeai.2025.100371 [Google Scholar] [Crossref]

13. Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00426-1 [Google Scholar] [Crossref]

14. Li, B., Tan, Y. L., Wang, C., & Lowell, V. (2025). Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching. Computers and Education: Artificial Intelligence, 100445. [Google Scholar] [Crossref]

15. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71 [Google Scholar] [Crossref]

16. Qu, X., & Wu, X. (2024). Understanding students’ adoption of ChatGPT in English language learning: The role of motivation and perceived usefulness. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12598-y [Google Scholar] [Crossref]

17. Sharadgah, T. A., & Sa'di, R. A. (2022). A systematic review of artificial intelligence technology use in English language teaching and learning. Journal of Information Technology Education: Research, 21, 401–427. https://doi.org/10.28945/4999 [Google Scholar] [Crossref]

18. Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8(45). https://doi.org/10.1186/1471-2288-8-45 [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles