Guidelines for AI Competency Development to Enhance Excellence in Educational Management of Higher Education Institutions in Bangkok Metropolitan
Keywords:
AI Competency, Excellence, Educational Management, Higher Education Institutions, BangkokAbstract
This research aimed to investigate the characteristics and components of AI competency, and to identify guidelines for its development to enhance excellence in the educational management of higher education institutions in the Bangkok Metropolitan area. This was achieved through a study of documents and empirical data, including in-depth interviews with 12 successful administrators. The findings were subsequently used to develop a rating scale questionnaire based on a three-dimensional AI competency framework: AI literacy, AI tool utilization and problem-solving, and adaptation to AI-driven changes. This questionnaire was administered to 598 administrators and personnel of higher education institutions in the Bangkok Metropolitan area, employing a mixed-methods research design combining quantitative and qualitative approaches. Data analysis involved exploratory factor analysis, data triangulation, and expert-based focus group discussions to validate the proposed guidelines. The research findings revealed three characteristics of AI competency: (1) AI literacy, (2) AI tool utilization and problem-solving, and (3) adaptation to AI-driven changes. The main components for developing AI competency to enhance excellence in educational management included: (1) the cognitive domain, (2) the psychomotor domain, and (3) the affective domain. The sub-components comprised: (1) computer and AI fundamentals, (2) AI accessibility, (3) AI utilization, (4) AI media production and creation, (5) AI communication, (6) AI media management, and (7) AI evaluation. There were a total of 195 indicators, all of which could explain 72.956 percent of AI competency. The guidelines for developing AI competency to enhance excellence in educational management involved five methods: (1) self-directed learning and development, (2) online learning, (3) case studies, (4) AI-assisted learning, and (5) workshops. These research results can be used to establish policies or mechanisms for administrators to implement in developing AI competency among personnel for effective and efficient educational management in the digital education era at the higher education level, ultimately striving for excellence.
References
Aad, S., & Hardey, M. (2025). Generative AI: Hopes, controversies and the future of faculty roles in education. Quality Assurance in Education, 33(2), 267–282.
Agila-Palacios, M. V., Muñoz-Repiso, A. G. V., & Ramírez-Montoya, M. S. (2022). Influence of active methodologies: Projects and cases in the development of AI competences with mobile devices. Journal of Applied Research in Higher Education, 14(3), 1007–1020.
Ahmed, S. F., Alam, M. S. B., Hassan, M., Rozbu, M. R., Ishtiak, T., Rafa, N., & Gandomi, A. H. (2023). Deep learning modelling techniques: Current progress, applications, advantages, and challenges. Artificial Intelligence Review, 56, 13521–13617.
Bodiako, A. V., Ponomareva, S. V., Rogulenko, T. M., Melnik, M. V., & Gorlov, V. V. (2021). Professional and qualification potential of the digital society: Indicative evaluation and systemic management. International Journal of Sociology and Social Policy, 41(1/2), 50–61.
European Commission. (2019). The digital competence framework 2.0. https://joint-research-centre.ec.europa.eu/oldpage-digcomp/digcomp-framework_en
Guo, M., Gu, M., & Huo, B. (2025). The impacts of automation and augmentation AI use on physicians’ performance: An ambidextrous perspective. International Journal of Operations & Production Management, 45(1), 114–151.
Hao, X., & Demir, E. (2024). Artificial intelligence in supply chain decision-making: An environmental, social, and governance triggering and technological inhibiting protocol. Journal of Modelling in Management, 19(2), 605–629.
Holmes, J., Moraes, O. R., Rickards, L., Steele, W., Hotker, M., & Richardson, A. (2022). Online learning and teaching for the SDGs – exploring emerging university strategies. International Journal of Sustainability in Higher Education, 23(3), 503–521.
Jafari, F., & Keykha, A. (2024). Identifying the opportunities and challenges of artificial intelligence in higher education: A qualitative study. Journal of Applied Research in Higher Education, 16(4), 1228–1245.
Kang, H. (2023). Artificial intelligence and its influence in adult learning in China. Higher Education, Skills and Work-Based Learning, 13(3), 450–464.
Lee, J. J., & Meng, J. (2021). Digital competencies in communication management: A conceptual framework of readiness for industry 4.0 for communication professionals in the workplace. Journal of Communication Management, 25(4), 417–436.
Mambile, C., & Mwogosi, A. (2025). Transforming higher education in Tanzania: Unleashing the true potential of AI as a transformative learning tool. Technological Sustainability, 4(1), 51–76.
Marengo, A., Pagano, A., Pange, J., & Soomro, K.A. (2024). The educational value of artificial intelligence in higher education: A 10-year systematic literature review. Interactive Technology and Smart Education, 21(4), 625–644.
National Information Technology Committee. (2019). The essential digital competencies for undergraduate students in Thai higher education institutions. https://www.nectec.or.th/en/wp-content/uploads/2021/07/NECTEC-Annual-Report-2019_ENG-compressed.pdf
Oladimeji, O. O. (2023). Machine learning in smart health research: A bibliometric analysis. International Journal of Information Science and Management, 21(1), 119–128.
Parkatti, A., Saari, T., Tammelin, M., & Villi, M. (2022). Framing digital competence in media work – The case of Finland. International Journal of Sociology and Social Policy, 42(13/14), 15–29.
Phakamach, P. (2023). Educational innovation: Elements and mechanisms for the development of Thai educational institutions towards internationalization. Journal of Education and Innovative Learning, 3(2), 161–179.
Phakamach, P., Panjarattanakorn, D., & Onsampant, S. (2023). Conceptualization and development of digital leadership to drive corporate digital transformation for sustainable success. International Journal of Educational Communications and Technology, 3(2), 30–42.
Phakamach, P., Senarith, P., & Wachirawongpaisarn, S. (2022). ICT systems development guidelines for educational innovation management of Rajamangala University of Technology in Thailand. Journal of Education and Innovative Learning, 2(2), 109–130.
Routray, R., & Khandelwal, K. (2024). Artificial intelligence (AI) adoption: Do Generation Z students feel technostress in deploying AI for completing courses of study at universities? Asian Education and Development Studies, 13(5), 534–545.
Saib, M. O., Rajkoomar, M., Naicker, N., & Olugbara, C. T. (2023). Digital pedagogies for librarians in higher education: A systematic review of the literature. Information Discovery and Delivery, 51(1), 13–25
Wang, Y. H., & Lin, G. Y. (2023). Exploring AI-healthcare innovation: Natural language processing-based patents analysis for technology-driven roadmapping. Kybernetes, 52(4), 1173–1189.
Yadav, A. K. S. (2022). The essential skills and competencies of LIS professionals in the digital age: Alumni perspectives survey. Global Knowledge, Memory and Communication, 71(8/9), 837–856.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 CUAST Journal
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
