The Mediating Effects of Artificial and Ethical Intelligence on the Relationship Between Pedagogical Competence and Preservice Teachers’ Performance
DOI:
https://doi.org/10.5281/zenodo.19258907Keywords:
pedagogical competence, artificial intelligence, ethical intelligence, mediation analysis, preservice teachers’ performanceAbstract
Behind every effective preservice teacher is a blend of competence, technology, and ethical insight. This study investigated the mediating effects of emerging technology and ethical intelligence on the relationship between pedagogical competence and preservice teachers’ performance. Using a cross-sectional predictive correlational research design with mediation analysis, the study involved 231 fourth-year preservice teachers from Region X who participated in the 2024 PAFTE ASTER 10 Conference. Validated instruments measured pedagogical competence, use of emerging technology, ethical intelligence, and teaching performance. Data were collected via Google Forms and analyzed in Jamovi, using statistical tools including the mean, standard deviation, Pearson product-moment correlation, and generalized linear model (GLM) mediation analysis. Results revealed that preservice teachers exhibited high levels of pedagogical competence, technology use, and ethical intelligence, particularly in empathetic engagement and professional integrity. Their performance was rated satisfactory in lesson planning, adaptive teaching, professional development, and collaboration. Significant correlations were found between pedagogical competence and performance, as well as between technology use and performance. Ethical intelligence also showed a meaningful relationship with performance. GLM mediation analysis showed that emerging technology partially mediated the relationship between pedagogical competence and performance. Although ethical intelligence was positively related to both pedagogical competence and technology use, it did not significantly mediate the direct relationship with performance. However, its indirect effect, in combination with technology, strengthened this relationship. Pedagogical competence significantly influences preservice teachers’ performance, and emerging technology further enhances this effect. Teacher education programs should intensify pedagogy training, integrate technology, and enrich ethical learning to improve professional readiness.
References
Acedo, C., & Tan, M. (2021). Educating for global competence in Southeast Asia. Prospects, 51, 15–30. https://doi.org/10.1007/s11125-020-09515-y
Akgün, S. and Greenhow, C. (2021). Artificial intelligence in education: addressing ethical challenges in k-12 settings. Ai and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7
Black, N., George, S., Eguchi, A., Dempsey, J., Langran, E., Fraga, L., … & Howard, N. (2024). A framework for approaching ai education in educator preparation programs. Proceedings of the Aaai Conference on Artificial Intelligence, 38(21), 23069-23077. https://doi.org/10.1609/aaai.v38i21.30351
Burton, S. (2011). Perspective consciousness and cultural relevancy: partnership considerations for the re-conceptualization of music teacher preparation. Arts Education Policy Review, 112(3), 122-129. https://doi.org/10.1080/10632913.2011.566082
Chen, L., Zhou, Y. F., & Nanakida, A. (2025). ‘I know I am caring’: fostering ethical care awareness and practice among pre-service early childhood teachers. Journal of Education for Teaching, 51(1), 61-78.
Cox, S., & Graham, C. R. (2021). Using TPACK as a framework for understanding teacher learning and technology integration. TechTrends, 65(2), 219–229. https://doi.org/10.1007/s11528-020-00564-8
D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. (2024). Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education. Medical Education Online, 29(1). https://doi.org/10.1080/10872981.2024.2330250
Göçen, A. and AYDEMİR, F. (2020). Artificial intelligence in education and schools. Research on Education and Media, 12(1), 13-21. https://doi.org/10.2478/rem-2020-0003
Jacob, F. I. L. G. O. N. A., John, S. A. K. I. Y. O., & Gwany, D. M. (2020). Teachers’ pedagogical content knowledge and students’ academic achievement: A theoretical overview. Journal of Global Research in Education and Social Science, 14(2), 14-44.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of ai ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. https://doi.org/10.1038/s42256-019-0088-2
Khreisat, M. N., Khilani, D., Rusho, M. A., Karkkulainen, E. A., Tabuena, A. C., & Uberas, A. D. (2024). Ethical implications of AI integration in educational decision making: Systematic review. Educational Administration: Theory and Practice, 30(5), 8521-8527.
Mardhatillah, M. (2023). Freedom to learn-independent campus: efl preservice teachers’ voice on their pedagogical competence. Al-Ishlah Jurnal Pendidikan, 15(4), 4472-4480. https://doi.org/10.35445/alishlah.v15i4.3104
Miftāḥ, M., Widiati, U., Wulyani, A., & Sharif, T. (2023). Strategies to develop preservice English teachers’ pedagogical competence: a focus on critical reflection as a potential strategy., 377-384. https://doi.org/10.2991/978-2-38476-054-1_33
Mouta, A., Torrecilla-Sánchez, E. M., & Pinto-Llorente, A. M. (2025). Comprehensive professional learning for teacher agency in addressing ethical challenges of AIED: Insights from educational design research. Education and Information Technologies, 30(3), 3343-3387.
Ng, P. T., Hairon, S., & Sim, J. B. Y. (2020). Values and competencies for future-ready learners: Implications for Southeast Asian teacher education. Asia Pacific Journal of Education, 40(3), 313–326. https://doi.org/10.1080/02188791.2020.1761779
Svetlova, E. (2022). Ai ethics and systemic risks in finance. Ai and Ethics, 2(4), 713-725. https://doi.org/10.1007/s43681-021-00129-1
Tirri, K., & Kuusisto, E. (2020). Ethical sensitivity in teaching and teacher education. Education Sciences, 10(6), 166. https://doi.org/10.3390/educsci10060166
Tondeur, J., Aesaert, K., Prestridge, S., & Consuegra, E. (2018). A multilevel analysis of what matters in the training of pre-service teachers' ict competencies. Computers & Education, 122, 32-42. https://doi.org/10.1016/j.compedu.2018.03.002
Tondeur, J., Braak, J., Siddiq, F., & Scherer, R. (2016). Time for a new approach to prepare future teachers for educational technology use: its meaning and measurement. Computers & Education, 94, 134-150. https://doi.org/10.1016/j.compedu.2015.11.009
Yu, L. and Yu, Z. (2023). Qualitative and quantitative analyses of artificial intelligence ethics in education using vosviewer and citnetexplorer. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1061778
