Generative AI in Southeast Asian TVET: A Systematic Review of Learning Outcomes, Ethics and Research Directions

Authors

DOI:

https://doi.org/10.62712/ijevs.v1i2.8

Keywords:

Academic integrity, ChatGPT, Generative artificial intelligence, Southeast Asia, Technical and vocational education and training

Abstract

Background: Generative artificial intelligence tools such as ChatGPT entered technical and vocational education and training faster than evidence on their effects. Objective: This review synthesized empirical evidence on the applications, learning outcomes and ethical challenges of generative artificial intelligence in Southeast Asian vocational education. Method: Following PRISMA 2020, ten search strings were run in OpenAlex and Semantic Scholar for 2022–2026, which yielded 254 unique records, of which 25 primary studies met the eligibility criteria. Findings: The studies came from Indonesia (17), Malaysia (5) and Thailand (3), and 18 were published in 2026. Fourteen concerned English language learning. Four quasi-experimental studies reported gains in writing, speaking, writing self-efficacy and AI literacy, while most other evidence was self-reported, and no study measured hands-on technical competence. Academic integrity (9 studies), overreliance (7) and inaccurate output (5) were the most frequent risks, and privacy and unequal access were also reported. Benefits depended on teacher mediation, task design, AI literacy and institutional guidance. Implications: Institutions should favors guided over unrestricted use, and research should prioritize controlled, longitudinal studies with practical assessment. Contribution: The review offers the first region-specific evidence map and a framework for responsible integration.

Downloads

Download data is not yet available.

References

Apoko, T. W. (2025). Generative artificial intelligence in English instruction: Indonesian EFL vocational high school teachers' perspectives. Journal of Languages and Language Teaching, 13(3), 1432. https://doi.org/10.33394/jollt.v13i3.14190

Azlina, H., & Noh, N. S. (2025). Factors influencing the attitudes towards using ChatGPT for learning among marketing students at Politeknik Sultan Abdul Halim Mu'adzam Shah. Journal of STEM and Education, [volume(issue), pages]. https://openalex.org/W7219950743

Choeykhunthot, A., Limpinan, P., & Jantakoon, T. (2026). Extending UTAUT for generative AI adoption among vocational teachers: The roles of trust, AI literacy, and risk awareness. Higher Education Studies, 16(3), 565. https://doi.org/10.5539/hes.v16n3p565

Chooppawa, P., Limpinan, P., & Jantakoon, T. (2026a). Intention to use generative AI for vocational college administration. World Journal of Education, 16(3), 157. https://doi.org/10.5430/wje.v16n3p157

Chooppawa, P., Limpinan, P., & Jantakoon, T. (2026b). Acceptance of generative AI for supporting innovative learning in vocational education. World Journal of Education, 16(3), 30. https://doi.org/10.5430/wje.v16n3p30

Dinata, C., Milansari, I. L., Triyono, M. B., & Pratama, G. N. I. P. (2025). The potential of artificial intelligence in vocational education research and development: A bibliometric study. Jurnal Pendidikan Vokasi, 15(1), 59–74. https://doi.org/10.21831/jpv.v15i1.77873

Gulikers, J. T. M., Bastiaens, T. J., & Kirschner, P. A. (2004). A five-dimensional framework for authentic assessment. Educational Technology Research and Development, 52(3), 67–86. https://doi.org/10.1007/BF02504676

Halim, S., & Hairuddin, N. H. (2026). Vocational higher education students' perceptions on the use of artificial intelligence tools in learning English communication skills. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, [volume(issue), pages]. https://openalex.org/W7221274276

Hidayat, H., Muji, A. P., & Dewi, F. K. (2026). Estimating the effect of ChatGPT-assisted instruction on learning outcomes in TVET, vocational education, and engineering education: A meta-analysis. Journal of Information Technology Education: Research, 25, 35. https://doi.org/10.28945/5877

Indrayani, S., & Anjani, R. N. (2026). Enhancing vocational students' socio-emotional adjustment through artificial intelligence supported learning. AI and Developmental Insights in Education, 2(1), 144–158. https://doi.org/10.58524/aidie.v2i1.157

Janah, R., Tusino, T., & Dewi, P. (2026). Exploring the role of ChatGPT in developing writing skills and critical thinking among vocational high school students. AL-ISHLAH: Jurnal Pendidikan, 18(1). https://doi.org/10.35445/alishlah.v18i1.8580

Kardiyasa, I. G., Santosa, M. H., & Kusuma, I. P. I. (2026). The effect of ChatGPT on vocational students' writing and plagiarism awareness. Jurnal Ilmiah Global Education, 7(3), 2330–2334. https://doi.org/10.55681/jige.v7i3.6900

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., . . . Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Khor, M. S. C., Che' Lah, C. F., & Hamzah, R. H. (2026). AI usage patterns and effects on English language comprehension among students at Politeknik Kota Bharu. International Journal on e-Learning and Higher Education, 21(1), 1–20. https://doi.org/10.24191/ijelhe.v21n1.2111

Lestari, T. P. (2025). Analyzing the impact of artificial intelligence on student learning: A case study of SMK Tri Arga 2. Journal of Applied Informatics and Computing, 9(1), 221–226. https://doi.org/10.30871/jaic.v9i1.8902

Majid, N. W. A., Barri, M. A. F., Sari, A. P., Sodikin, R. A., Azman, M. N. A., & Prestoza, M. J. R. (2026). Vocational teachers' insights on artificial intelligence and computational thinking integration. Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika, 10(1), 1–15. https://doi.org/10.36312/e-saintika.v10i1.3660

Manan, N. A., Radzuan, N. R. M., & Masrom, U. K. (2026). Understanding English writing motivation among TVET learners: The role of ChatGPT in scriptwriting task. In Atlantis Advances in Applied Sciences (pp. 127–140). Atlantis Press. https://doi.org/10.2991/978-94-6239-745-3_10

Mariadass @ Manickam, J., Chyng, L. Y., & Gobal, N. R. (2026). Exploring ChatGPT utilization and ethical awareness in TVET education through the ABCE framework. International Journal of Software Engineering and Computer Systems, 12(1), 73–84. https://doi.org/10.15282/ijsecs.12.1.2026.7.0153

Moeis, D., Usman, N., Faisal, M., Harmin, A., Mulyadi, I., & Thamrin, M. (2024). Microsoft Copilot training for monitoring student learning: A case study vocational high school Makassar - Indonesia. I-Com: Indonesian Community Journal, 4(3), 1911–1922. https://doi.org/10.33379/icom.v4i3.5134

Mubarok, H., Rostika, Y., Komaro, M., & Saripudin. (2026). Defining, operationalizing, and measuring generative AI competence among vocational teachers: A scoping review. International Journal of Educational Practice and Policy, 4(3), 37–55. https://doi.org/10.66314/ijepp.v4i3.1182

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

Pebriani, S. R., Suryana, Y., & Yuniarti. (2025). Students' perceptions on the use of artificial intelligence (AI) as English learning tools at SMK Model Patriot IV Ciawigebang. Darussalam English Journal (DEJ), 5(2), 105–119. https://doi.org/10.30739/dej.v5i2.4008

Pranoto, D. C. Y., Rufi'i, R., Sabariah, S., & Bandono, A. (2025). Harnessing generative AI for ESP: A cross-disciplinary vocational education framework with predictive modeling evidence from Indonesia. International Journal of Artificial Intelligence Research, 9(1.1). https://doi.org/10.29099/ijair.v9i1.1.1569

Pratama, V., Tahrun, T., & Yukaman, H. (2026). Students' and teachers' perspectives on the use of AI chatbot in English language teaching at the vocational high school level in Methodist 2 Palembang. Esteem Journal of English Education Study Programme, 9(1), 930–943. https://doi.org/10.31851/b0j1dv33

Ratnaningsih, D. (2025). Enhancing students' speaking skills using ChatGPT application in ESP maritime English learning. JEES (Journal of English Educators Society), 10(2), 186–197. https://doi.org/10.21070/jees.v10i2.1964

Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/j.tics.2016.07.002

Samala, A. D., Zhai, X., Aoki, K., Bojic, L., & Zikic, S. (2024). An in-depth review of ChatGPT's pros and cons for learning and teaching in education. International Journal of Interactive Mobile Technologies (iJIM), 18(2), 96–117. https://doi.org/10.3991/ijim.v18i02.46509

Sardi, J., Darmansyah, Candra, O., Yuliana, D. F., Habibullah, Yanto, D. T. P., & Eliza, F. (2025). How generative AI influences students' self-regulated learning and critical thinking skills? A systematic review. International Journal of Engineering Pedagogy (iJEP), 15(1), 94–108. https://doi.org/10.3991/ijep.v15i1.53379

Sari, H. F. A., Pattipeilohy, V., & Putra, H. (2026). Can ChatGPT strengthen students' confidence in business email writing? A quantitative study of EFL learners' self-efficacy. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, [volume(issue), pages]. https://openalex.org/W7221275193

Subramaniam, R. (2026). Lecturers' perceptions of ChatGPT use in Malaysian polytechnic ESL classrooms: An exploratory descriptive study. International Journal of Humanities Philosophy and Language, 9(34), 32. https://doi.org/10.35631/ijhpl.934003

Sudarmaji, E., Herlan, Yatim, M. R., Yunas, S., Prakoso, R., Kaniati, R., Ramadh, O. T., & Juwanto, S. N. (2026). AI literacy and cognitive evolution in Generation Z: A synthesis of empirical evidence and workshop-based insights. Journal of Social Science and Human Research Studies, 2(4). https://doi.org/10.65150/ep-jsshrs/v2e4/2026-05

Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45

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. https://doi.org/10.2307/30036540

Weigel, T., Mulder, M., & Collins, K. (2007). The concept of competence in the development of vocational education and training in selected EU member states. Journal of Vocational Education & Training, 59(1), 53–66. https://doi.org/10.1080/13636820601145549

Yahya, S. M., Munir, & Ariyani, A. (2026). Improving SMK students' speaking skills with AI-based learning in vocational contexts: A quasi-experimental study. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, [volume(issue), pages]. https://openalex.org/W7221211561

Yuniarti, Y., & Pebriani, S. R. (2026). Vocational high school students' perceptions of using AI for learning English: Benefits and challenges. Journal of English Educational Study (JEES), 9(1), 36–45. https://doi.org/10.31932/jees.v9i1.5448

Yusuf, W. F., Imelda, N. F., & Kholiq, A. (2026). Integration of artificial intelligence in Islamic religious education learning in vocational schools. MUMTAZ: Jurnal Pendidikan Agama Islam, 6(1), 173–195. https://doi.org/10.69552/mumtaz.v6i1.3753

Downloads


Published

2026-11-01