Familiarity and perception of AI in Teacher Education: factors influencing its acceptance and use
Parole chiave:
Artificial intelligence, Teacher training, Human validation, PerceptionAbstract
Artificial Intelligence (AI) is emerging as a potentially transformative resource in teacher education, yet its adoption is influenced by multiple factors. This study examines pre-service teachers' perceptions of AI, exploring key concerns, perceived limitations, and the role of familiarity with this technology. Particular attention is given to the need for human validation in automated decisions and the aspects requiring improvement to foster the effective integration of AI in teacher training. The findings provide insights to guide educational policies and promote a conscious and critical use of AI in knowledge construction.
Riferimenti bibliografici
Chee, H., Ahn, S., & Lee, J. (2024). A competency framework for AI literacy: Variations by different learner groups and an implied learning pathway. British Journal of Educational Technology, 55(1), 123-145. https://doi.org/10.1111/bjet.13556
Chounta, I. A., Bardone, E., Raudsep, A. et al. (2022). Exploring Teachers’ Perceptions of Artificial Intelli-gence as a Tool to Support their Practice in Estonian K-12 Education. International Journal of Arti-ficial Intelligence in Education 32, 725–755 . https://doi.org/10.1007/s40593-021-00243-5.
Cukurova, M., Miao, X., & Brooker, R. (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement. International conference on artificial intelligence in education (pp. 151–163). Springer. http://doi.org/10.1007/978-3-031-36272-9_13
European Commission (2022) Ethical guidelines for educators on the use of artificial intelligence and data in teaching and learning. Publications Office of the European Union. https://doi.org/10.2766/127030
European Commission (2022) Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://doi.org/10.2766/153756
European Parliament & Council of the European Union (2024) Regulation (EU) 2024/1689 of 13 June 2024 establishing harmonized rules on artificial intelligence. Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng
Holmes, W. & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Edu-cation, 57, 542–570. https://doi.org/10.1111/ejed.12533
Kelly, S., Kaye, S. A., & Oviedo-Trespalacios, O. (2022). What factors contribute to acceptance of artificial intelligence? a systematic review. Telematics and Informatics,101925. https://doi.org/10.1016/j.tele.2022.101925
Kizilcec, R. F. (2023). To advance ai use in education, focus on understanding educators. International Journal of Artificial Intelligence in Education,1–8. https://doi.org/10.1007/s40593-023-00351-4
Lukyanenko, R., Maass, W., & Storey, V. C. (2022). Trust in artificial intelligence: From a foundational trust framework to emerging research opportunities. Electronic Markets, 32(4), 1993–2020. https://doi.org/10.1007/s12525-022-00605-4
Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers' trust in AI-powered educa-tional technology and a professional development program to improve it. British Journal of Educa-tional Technology, 53, 914–931. https://doi.org/10.1111/bjet.13232
Parsons, D., Maccallum K., Schofield L., Johnstone A., & Coulter S.K. (2020). Next-generation digital cur-ricula for future teaching and learning. In Yu S., Ally M., Tsinakos A., Emerging Technologies and Pedagogies in the Curriculum. Springer.
Perla, L., Agrati, L. S., & Beri, A. (2025). Post-teaching and professional learning: an investigation on teachers attitudes towards AI. Professional Development in Education, 1–12. https://doi.org/10.1080/19415257.2025.2465970
Perla, L., Amati, I., De Feo, A., Di Grassi, A., Forliano, R., & Santacroce, M.T. (2024). Didattica algoretica e Linee guida per la progettazione di ambienti di apprendimento human-centered. Medical Humanities & Medicina Narrativa, 2(5), 183-200. https://doi.org/10.53136/979122181616711
Rogerson, A., Hankins, E., Fuentes Nettel, P., & Rahim, S. (2022). Government ai readiness index 2022. Oxford Insights.
Romero, M., Frøsig, T., Taylor-Beswick, A. M., Laru, J., Bernasco, B., Urmeneta, A., & Girard, M. A. (2024). Manifesto in Defence of Human-Centred Education in the Age of Artificial Intelligence. In Creative Applications of Artificial Intelligence in Education (pp. 157-178). Cham: Springer Nature Switzerland.
Romero, M. & Heiser, L. (Dir.) (2023). Enseigner et apprendre à l’ère de l’intelligence artificielle. Canopé, Livre blanc. hal-04013223v2.
Touretzky, D. S., & Gardner-McCune, C. (2022). Artifical Intelligence Thinking in K-12. In S.-C. Kong and H. Abelson (Eds.), Computational Thinking in K-12: Artificial Intelligence Literacy and Physical Computing. MIT Press.
UNESCO (2024). AI competency framework for teachers. https://doi.org/10.54675/ZJTE2084
Viberg, O., Cukurova, M. & Feldman-Maggor, Y. et al. (2024). What Explains Teachers’ Trust in AI in Education Across Six Countries?. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00433-x.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on ar-tificial intelligence applications in higher education-where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0
##submission.downloads##
Pubblicato
Come citare
Fascicolo
Sezione
Licenza
Copyright (c) 2025 Viviana Vinci, Pierangelo Berardi
Questo lavoro è fornito con la licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 4.0 Internazionale.
