Authors
- kholamhosein bagherabadi 1
- Seyed Mohammad Reza, emam jome, 2
- Seydarsoul, Emadi, 3
- ,, Alireza Osare 4
- Zahra Shirmohammadi 5
1 Educational Sciences, Tarbiat University, Secretary, Rajaei University, Tehran, Faculty of Humanities
2 Emam jome, S, Associate Professor, Educational Sciences, Department of Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
3 Emadi, S, Associate Professor, Educational Sciences, Department of Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
4 osare, A. Professor,Educational Sciences, Department of Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
5 , Zahra, Sh, Associate Professor,Department of Computer Systems Architecture, Faculty of Computer Engineering, Academic , Shahid Rajaee Teacher Training University, Tehran, Iran
Abstract
Background and Purpose: Artificial intelligence (AI) has emerged as a transformative force in education, offering new possibilities for enhancing teaching and learning quality, enabling adaptive assessment, redesigning instructional experiences, and empowering future teachers. Despite these affordances, its adoption raises critical ethical, organizational, and pedagogical concerns. Against this backdrop, the present study aimed to systematically synthesize research published between 2020 and 2025 to identify key opportunities and challenges in integrating AI into teacher education curricula.
Method: Guided by the PRISMA framework, this research synthesis examined thirty eligible studies. Data were analyzed through multi-stage coding, including open, axial, and selective coding, to extract themes and develop an integrative understanding.
Findings: The synthesis highlighted substantial opportunities afforded by AI in teacher education, such as personalized learning, real-time formative feedback, data-driven decision-making, innovative lesson design and simulation-based training, reduction of administrative workload, and cultivation of technological and professional competencies. Challenges identified included ethical and legal concerns, algorithmic bias and threats to equity, infrastructural gaps and unequal access, limited AI literacy, cultural resistance, and questions regarding authenticity of AI-based assessment practices.
Conclusion: The findings underscore the necessity of systematic capacity-building for responsible adoption of AI in teacher education. This requires transparent policy development, investment in technological infrastructure, continuous professional learning for teachers, and proactive cultural change management. Ultimately, integrating AI into teacher education represents not merely a technological advancement but a systemic and cultural transformation demanding attention to policy, institutional, and individual dimensions.
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