School leadership, Artificial Intelligence, and the ethical imperative in the STEM approach

Authors

DOI:

https://doi.org/10.31207/colloquia.v12i1.190

Keywords:

STEM education, technological ethics, social justice, artificial intelligence, educational leadership

Abstract

The integration of Artificial Intelligence (AI) into education, within the framework of the STEM (Science, Technology, Engineering, and Mathematics) approach, poses a crucial challenge that transcends mere technical optimization to advance educational justice. This qualitative research aimed to understand how school leadership and ethics in the use of AI impact the meaningful and transformative implementation of the STEM approach in secondary education institutions. Semi-structured interviews were conducted with school principals with a history of innovation. The results reveal an incipient understanding of the pedagogical and ethical dimensions of AI, which limits its transformative potential. However, critical factors are identified that must be considered for the successful implementation of STEM: distributed leadership, a collaborative teaching culture, and an explicit ethical commitment. It is concluded that school leadership is crucial in incorporating and guiding AI in the service of transformative objectives such as developing critical thinking and reducing structural gaps, ensuring that STEM education becomes a tool for social justice and equity.

References

Barkoczi, N., Maier, M., & Horvat-Marc, A. (2024). The impact of artificial intelligence on personalized learning in STEM education. In INTED2024 Proceedings (pp. 4980–4989). IATED. https://doi.org/10.21125/inted.2024.1289

Barton, A., & Tan, E. (2010). We be burnin’! Agency, identity, and science learning. Journal of the Learning Sciences, 19(2), 187–229. https://doi.org/10.1080/10508400903530044

Boateng, O., & Boateng, B. (2025). Algorithmic bias in educational systems: Examining the impact of AI-driven decision making in modern education. World Journal of Advanced Research and Reviews, 25(1), 2012–2017. https://doi.org/10.30574/wjarr.2025.25.1.0253

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Calabrese Barton, A. (2002). Urban science education studies: A commitment to equity, social justice and a sense of place. Studies in Science Education, 38(1), 1–37. https://doi.org/10.1080/03057260208560186

Cheah, Y. H., & Kim, J. (2025). STEM teachers' perceptions, familiarity, and support needs for integrating generative artificial intelligence in K-12 education. School Science and Mathematics. Advance online publication. https://doi.org/10.1111/ssm.18334

Chen, H. (2024). The ethical challenges of educational artificial intelligence and coping measures: A discussion in the context of the 2024 World Digital Education Conference. Science Insights Education Frontiers, 20(2), 3263–3281. https://doi.org/10.15354/sief.24.re339

Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, Article 100002. https://doi.org/10.1016/j.caeai.2020.100002

Fraser, N. (2008). La justicia social en la era de la globalización: Redistribución, reconocimiento y participación. Distintas Latitudes. Revista de Trabajo, 4(6), 83–99. https://www.bibliotecafragmentada.org/wp-content/uploads/2023/12/Fraser_justicia-social.pdf

Harris, A., & Jones, M. (2023). Compassionate leadership. School Leadership & Management, 43(3), 185–188. https://doi.org/10.1080/13632434.2023.2235540

Leithwood, K., & Sun, J. (2012). The nature and effects of transformational school leadership: A meta-analytic review of unpublished research. Educational Administration Quarterly, 48(3), 387–423. https://doi.org/10.1177/0013161X11436268

Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: Guidance for policy-makers. UNESCO. https://doi.org/10.54675/pcsp7350

Selwyn, N. (2024). On the limits of artificial intelligence (AI) in education. Nordic Journal of Pedagogy and Critique, 10, 3–14. https://doi.org/10.23865/ntpk.v10.6062

Shields, C. M. (2017). Transformative leadership in education: Equitable and socially just change in an uncertain and complex world (2nd ed.). Routledge. https://doi.org/10.4324/9781315207148

Southgate, E. (2020). Artificial intelligence, ethics, equity and higher education: A technical report. National Centre for Student Equity in Higher Education, Curtin University.

Spillane, J. P. (2005). Distributed leadership. The Educational Forum, 69(2), 143–150. https://doi.org/10.1080/00131720508984678

Tate, W. F. (2001). Science education as a civil right: Urban schools and opportunity-to-learn considerations. Journal of Research in Science Teaching, 38(9), 1015–1028. https://doi.org/10.1002/tea.1045

Zhan, Z., & Niu, S. (2023). Subject integration and theme evolution of STEM education in research from preschool to secondary and higher education. Humanities and Social Sciences Communications, 10, Article 781. https://doi.org/10.1057/s41599-023-02303-8

Published

2025-12-20

Issue

Section

Dossier: Artificial Intelligence: Convergences, Challenges, and Transformations in the Contemporary World