Integrating Artificial Intelligence and the Tri-sikkha in Educational Administration for Sustainable Development.
Article Sidebar
Main Article Content
Abstract
Training (Tri-sikkha: Sila, Samadhi, and Paññā) in educational administration for sustainable development. This is achieved through an analysis of AI's potential and limitations, combined with Buddhist philosophy to provide value-based governance. The research presents a three-level conceptual model: a foundation of “Sila” (Ethical Conduct) to establish ethical frameworks, data protection, transparency, and the prevention of algorithmic bias; a core of “Samadhi” (Concentration) for the mindful governance of AI systems, focusing on educational goals and maintaining a balance between technology and human interaction; and an apex of “Paññā” (Wisdom) to foster holistic, forward-thinking decision-making and create collective intelligence between humans and machines.
The article outlines practical guidelines at the policy, institutional, and operational levels, illustrated with a case study of a student risk-alert system that reflects the application of the Threefold Training as an ethical compass. Furthermore, it analyzes technical, organizational, and ethical challenges, providing preliminary recommendations that include developing Explainable AI (XAI), creating common data standards, implementing holistic change management, and establishing a Regulatory Sandbox for AI ethics. In conclusion, the Threefold Training can serve as a philosophical framework to guide the use of AI in educational administration, ensuring its application is effective, aligned with human values, and supportive of achieving sustainable educational goals.
Article Details
References
พระพรหมคุณาภรณ์ (ป.อ.ปยุตฺโต). (2560). พุทธธรรม ฉบับปรับปรุงและขยายความ. สำนักพิมพ์ผลิธัมม์.
พระพรหมคุณาภรณ์ (ป. อ.ปยุตฺโต). (2561). พุทธธรรม ฉบับปรับปรุงและขยายความ. โรงพิมพ์มหาจุฬาลงกรณราชวิทยาลัย.
Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6, 52138-52160. https://doi.org/10.1109/ACCESS.2018.2870052
Baker, T., & Smith, L. (2022). Artificial intelligence in educational administration: A practical guide. Routledge.
Bayamlıoğlu, E. (2021). The right to explanation, the right to contest and the GDPR. In M. Hildebrandt & K. O'Hara (Eds.), Life and the law in the era of data-driven agency (pp. 133-150). Edward Elgar Publishing.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
Chen, X., Lee, C., & Wang, H. (2023). A systematic review of big data analytics in education: Trends and challenges. Educational Technology & Society, 26(1), 112- 128.
Daniel, B. K. (2019). Big data and data science: A critical review of the literature. International Journal of Educational Technology in Higher Education, 16(1), Article 40. https://doi.org/10.1186/s41239-019-0174-z
Floridi, L., & Taddeo, M. (Eds.). (2018). The ethics of artificial intelligence. Springer.
Mittelstadt, B. D. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1(11), 501–507. https://doi.org/10.1038/s42256-019-0114-4
Hallinger, P., & Heck, R. H. (2019). Leadership for learning: A review of the research and a proposed conceptual framework. In M. Connolly, D. H. Eddy-Spicer, C. James, & S.
Hallinger, P., & Lu, J. (2023). A systematic review of research on the roles of school leaders in technology-rich environments. Educational Management Administration & Leadership, 51(1), 4-25. https://doi.org/10.1177/1741143221993297
Kim, J., & Lee, S. (2021). The mindful leader: Integrating eastern philosophy with western management theory. Journal of Management & Spirituality, 18(2), 115-130.
Kuner, C., Cate, F. H., Millard, C., & Svantesson, D. J. B. (2020). The Cambridge handbook of consumer privacy. Cambridge University Press.
O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Selwyn, N. (2021). Education and technology: Key issues and debates (3rd ed.). Bloomsbury Academic.
Shneiderman, B. (2022). Human-centered AI. Oxford University Press.
UNESCO. (2021). AI and education: Guidance for policy-makers. United Nations Educational, Scientific and Cultural Organization.
United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development. Retrieved from https://sdgs.un.org/2030agenda
Williamson, B. (2017). Big data in education: The digital future of learning, policy and practice. Sage Publications.
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(1), Article 39
