THE EFFECTIVENESS OF THE UTILIZATION OF THE ARTIFICIAL INTELLIGENCE (AI) TOOLS IN IMPROVING THE SCHOOL HEADS’ TECHNICAL SKILLS IN THE PUBLIC ELEMENTARY SCHOOLS IN THE DIVISION OF QUEZON
Keywords:
artificial intelligence, school leadership, technical skills, educational management, ChatGPT, public elementary schools, PhilippinesAbstract
Artificial intelligence (AI) is increasingly positioned as a support tool for school leadership, yet evidence on how Philippine public elementary school heads actually use AI, and how effective it is for their day-to-day technical work, remains limited, particularly at the division level. Objective: This study determined the extent of utilization and effectiveness of AI tools (ChatGPT, Microsoft Copilot, Google Workspace AI, Canva AI, and Grammarly) in improving the technical skills of public elementary school heads in the Division of Quezon, Philippines, and identified the challenges encountered and the solutions offered. Using a descriptive-evaluative-correlational design, a researcher-made, adviser-validated questionnaire (reliability r = .78) was administered through total enumeration of a Slovin-derived sample of 263 school heads across four congressional districts, drawn from a population of 771 elementary schools. Data were analyzed using weighted means and Kendall's Coefficient of Concordance (W) with chi-square tests at α = .05. Results: AI tools were Much Utilized overall (grand mean = 4.30), led jointly by ChatGPT and Canva AI (4.38 each). AI use was rated Much Effective overall (grand mean = 3.90) in improving technical skills, most strongly for Developing Self and Others (4.16) and least for Leading Strategically (3.62). Challenges were rated Fairly Challenging overall (grand mean = 2.43), concentrated in Budget Planning and Allocation Support (2.92). Proposed solutions were rated Very Much Necessary (grand mean = 4.87). Agreement in rank orders across congressional districts was statistically significant for most, but not all, sub-areas. AI tools are already embedded in the routine technical work of school heads and are perceived as effective, but their contribution to higher-order strategic leadership and financial management lags behind administrative and instructional support functions, pointing to a targeted capacity-building and policy agenda rather than a technology-access problem alone.
References
Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30.
Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
Bass, B. M. (1985). Leadership and performance beyond expectations. Free Press.
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape. Sustainability, 13(2), 800.
Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton.
Burns, J. M. (1978). Leadership. Harper & Row.
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), 22.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Dwivedi, Y. K., et al. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges, and implications of generative conversational AI. International Journal of Information Management, 71, 102642.
Miao, F., & Holmes, W. (2021). Guidance for policy-makers on AI and education. UNESCO.
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy. Computers and Education: Artificial Intelligence, 2, 100041.
OECD. (2021). OECD digital education outlook 2021: Pushing the frontiers with artificial intelligence, blockchain and robots. OECD Publishing.
OECD. (2023). Digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing.
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning. Research and Practice in Technology Enhanced Learning, 12(1), 1–13.
Republic Act No. 10173. (2012). Data Privacy Act of 2012.
Republic Act No. 7160. (1991). Local Government Code of the Philippines.
Republic Act No. 8525. (1998). Adopt-a-School Act.
Republic Act No. 9155. (2001). Governance of Basic Education Act.
Rogers, E. M. (1962). Diffusion of innovations. Free Press.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Susskind, R., & Susskind, D. (2015). The future of the professions. Oxford University Press.
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel? ChatGPT as a case study of generative artificial intelligence in education. Smart Learning Environments, 10(1), 15.
Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38.
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on AI applications in higher education. International Journal of Educational Technology in Higher Education, 16(39), 1–27.
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