Abstract
The integration of artificial intelligence (AI) into education has increased the need to strengthen teacher training to ensure its effective pedagogical implementation. This study aimed to analyze recent scientific evidence on teacher training in AI and its contribution to educational quality. A qualitative systematic review was conducted in accordance with the PRISMA guidelines, including twenty Scopus-indexed studies published between 2023 and 2025. The findings indicate that AI literacy, continuous professional development, and active training strategies constitute the main pillars of teacher preparation. The evidence also shows that AI enhances personalized learning, inclusion, and pedagogical innovation when implemented within sound ethical principles and pedagogical foundations. It is concluded that teacher training represents a key factor in achieving the responsible and sustainable integration of artificial intelligence aimed at strengthening educational quality.
References
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[2] D. A. Schön, The Reflective Practitioner: How Professionals Think in Action. New York, NY, USA: Basic Books, 1983.
[3] A. Brandão, L. Pedro, and N. Zagalo, “Teacher professional development for a future with generative artificial intelligence: An integrative literature review,” Digital Education Review, vol. 45, pp. 151–157, 2024, doi: 10.1344/der.2024.45.151-157.
[4] X. Tan, G. Cheng, and M. H. Ling, “Artificial intelligence in teaching and teacher professional development: A systematic review,” Computers and Education: Artificial Intelligence, vol. 8, Art. no. 100355, 2025, doi: 10.1016/j.caeai.2024.100355.
[5] S. Dogan, U. Y. Nalbantoglu, I. Celik, and N. Agacli Dogan, “Artificial intelligence professional development: A systematic review of TPACK, designs, and effects for teacher learning,” Professional Development in Education, 2025, doi: 10.1080/19415257.2025.2454457.
[6] J. Garzón, E. Patiño, and C. Marulanda, “Systematic review of artificial intelligence in education: Trends, benefits, and challenges,” Multimodal Technologies and Interaction, vol. 9, no. 8, Art. no. 84, 2025, doi: 10.3390/mti9080084.
[7] G. Erdem Coşgun, “Artificial intelligence literacy in assessment: Empowering pre-service teachers to design effective exam questions for language learning,” British Educational Research Journal, vol. 51, pp. 2340–2357, 2025, doi: 10.1002/berj.4177.
[8] A.-C. E. Ding, L. Shi, H. Yang, and I. Choi, “Enhancing teacher AI literacy and integration through different types of cases in teacher professional development,” Computers and Education Open, vol. 5, Art. no. 100178, 2024, doi: 10.1016/j.caeo.2024.100178.
[9] L. Kohnke, D. Zou, A. W. Ou, and M. M. Gu, “Preparing future educators for AI-enhanced classrooms: Insights into AI literacy and integration,” Computers and Education: Artificial Intelligence, vol. 6, Art. no. 100398, 2025, doi: 10.1016/j.caeai.2025.100398.
[10] B. Pei, J. Lu, and X. Jing, “Empowering preservice teachers’ AI literacy: Current understanding, influential factors, and strategies for improvement,” Computers and Education: Artificial Intelligence, vol. 6, Art. no. 100406, 2025, doi: 10.1016/j.caeai.2025.100406.
[11] L. Guan, Y. Zhang, and M. M. Gu, “Pre-service teachers’ preparedness for AI-integrated education: An investigation from perceptions, capabilities, and teachers’ identity changes,” Computers and Education: Artificial Intelligence, vol. 6, Art. no. 100341, 2025, doi: 10.1016/j.caeai.2024.100341.
[12] J. Laru, I. Celik, I. Jokela, and K. Mäkitalo, “The antecedents of pre-service teachers’ AI literacy: Perceptions about own AI-driven applications, attitude towards AI and knowledge in machine learning,” European Journal of Teacher Education, 2025, doi: 10.1080/02619768.2025.2535623.
[13] Z. Li, C. Wang, and C. J. Bonk, “Generative AI for teachers’ self-directed professional development: A mixed-methods study,” TechTrends, 2025, doi: 10.1007/s11528-025-01123-8.
[14] M. Lucas, P. Bem-haja, Y. Zhang, C. Llorente-Cejudo, and A. Palacios-Rodríguez, “A comparative analysis of pre-service teachers’ readiness for AI integration,” Computers and Education: Artificial Intelligence, vol. 6, Art. no. 100396, 2025, doi: 10.1016/j.caeai.2025.100396.
[15] B. L. Moorhouse, Y. Wan, C. Wu, L. Kohnke, and T. Y. Ho, “Developing language teachers’ professional generative AI competence: An intervention study in an initial language teacher education course,” System, vol. 122, Art. no. 103399, 2024, doi: 10.1016/j.system.2024.103399.
[16] H. Galindo-Domínguez, N. Delgado, D. Losada, and J.-M. Etxabe, “An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective,” Journal of Digital Learning in Teacher Education, 2024, doi: 10.1080/21532974.2023.2284726.
[17] X. Han, “Improving pre-service teachers’ AI competencies: A quasi-experimental study,” Frontiers in Psychology, 2025, doi: 10.3389/fpsyg.2025.1642465.
[18] U. J. Ofem et al., “Teachers’ preparedness for the utilization of artificial intelligence in classroom assessment,” Frontiers in Education, 2025, doi: 10.3389/feduc.2025.1568306.
[19] C. N. Prilop et al., “Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI-enhanced methods,” Computers and Education: Artificial Intelligence, 2025, doi: 10.1016/j.caeai.2025.100471.
[20] Y. Lan, “Through tensions to identity-based motivations: Exploring teacher professional identity in artificial intelligence-enhanced teacher training,” Teaching and Teacher Education, vol. 137, Art. no. 104736, 2024, doi: 10.1016/j.tate.2024.104736.
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