HUMAN-CENTERED AI INTEGRATION IN VOCATIONAL EDUCATION IN THAILAND: CLASSROOM REALITIES AND EDUCATION ADAPTATION
DOI:
https://doi.org/10.64186/jsp3762Keywords:
Human-Centered AI, Thai Vocational Education, AI-Supported Learning, Digital Readiness, Teacher FacilitationAbstract
This research aimed to explore the implementation of generative AI within Thai vocational education classrooms, assess its impact on students' learning outcomes and behavioral engagement, and identify critical success factors and practical challenges for effective AI integration. Employing an explanatory sequential mixed-methods design grounded in human-centered AI integration theory, the study involved 200 vocational students selected via cluster random sampling and 5 teachers selected using a purposive sampling technique. Data were collected using questionnaires, observation forms, student reflections, and semi-structured interviews, then analyzed through descriptive statistics and content analysis. The findings revealed that generative AI was primarily integrated into three main instructional activities: brainstorming, project preparation, and presentation design, functioning strictly as a learning facilitator rather than a replacement for cognitive processing. Regarding the impacts on learners, quantitative results demonstrated the highest level of overall student engagement and perceived learning outcomes (Overall Mean = 4.66, S.D. = 0.47). However, qualitative data indicated that participant experiences remained inconsistent due to disparities in digital readiness, necessitating a pedagogical shift prioritizing teacher guidance. Furthermore, the investigation identified significant contextual factors and practical challenges acting as high-level constraints (Overall Mean = 4.48, S.D. = 0.68), including unequal digital access, internet instability, and students' overreliance on automated content. Ultimately, the study highlights that meaningful educational transformation involving AI is not driven by technology alone, but requires a complex negotiation of human relationships, active teacher facilitation, learner diversity, and institutional realities.
References
Best, J. W. (1981). Research in education (4th ed.). Prentice Hall of India.
Bruner, J. S. (1966). Toward a theory of instruction. Belknap Press of Harvard University Press.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among
five approaches (4th ed.). SAGE Publications.
Flick, U. (2018). An introduction to qualitative research (6th ed.). SAGE Publications.
Fullan, M. (2013). Stratosphere: Integrating technology, pedagogy, and change knowledge.
Pearson.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and
implications for teaching and learning. Center for Curriculum Redesign.
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., Pfeiffer, F., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Wagner, M., & Kasneci, G.
(2023). ChatGPT for good? On opportunities and challenges of large language models
for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274 DOI: https://doi.org/10.1016/j.lindif.2023.102274
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO.
https://doi.org/10.54675/EWZM9535 DOI: https://doi.org/10.54675/EWZM9535
Ministry of Education. (2024). Policy and focus of the Ministry of Education for fiscal year
https://www.moe.go.th/360policy-and-focus-moe-fiscal-year-2024/
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A
framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
https://doi.org/10.1111/j.1467-9620.2006.00684.x DOI: https://doi.org/10.1111/j.1467-9620.2006.00684.x
Nguyen, L. T., Kanjug, I., Lowatcharin, G., Manakul, T., Poonpon, K., Sarakorn, W., Somabut, A.,
Srisawasdi, N., Traiyarach, S., & Tuamsuk, K. (2022). How teachers manage their
classroom in the digital learning environment - Experiences from the University Smart Learning Project. Heliyon, 8(10), Article e10817. https://doi.org/10.1016/j.heliyon.2022.e10817 DOI: https://doi.org/10.1016/j.heliyon.2022.e10817
OECD. (2021). OECD digital education outlook 2021: Pushing the frontiers with artificial
intelligence, blockchain and robots. https://doi.org/10.1787/589b283f-en DOI: https://doi.org/10.1787/589b283f-en
Selwyn, N. (2016). Education and technology: Key issues and debates. (2nd ed.). Bloomsbury DOI: https://doi.org/10.5040/9781474235952
Academic.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive
Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4 DOI: https://doi.org/10.1207/s15516709cog1202_4
UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO Publishing. DOI: https://doi.org/10.54675/PCSP7350
UNESCO-UNEVOC. (2021). Reimagining technical and vocational education and training for
the post-COVID-19 era. UNESCO-UNEVOC International Centre.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes
(M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press.
World Economic Forum. (2023). The future of jobs report 2023.
https://www.weforum.org/publications/the-future-of-jobs-report-2023/
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of
research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0 DOI: https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2026 Journal of social studies perspectives
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The article is published under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license, which allows others to share the article while giving appropriate credit to the author. It prohibits the use of the article for commercial purposes or the creation of derivative works. Any other reuse or reproduction requires permission from the journal.
