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PEER-REVIEWED
Review
| Published: October 19, 2025
Can AI Enhance the Quality of Teacher Training? A Review-Based Study
Student, Netaji Subhash Open University, West Bengal, India
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Research Scholar, Department of Education, Sidho-Kanho-Birsha University, Purulia, West Bengal
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Assistant Professor, Department of Education, Sidho-Kanho-Birsha University, Purulia, West Bengal
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DIP: 18.01.025.20251304
DOI: 10.25215/1304.025
ABSTRACT
The emergence of Artificial Intelligence (AI) in education is transforming long-established approaches to teaching and learning. In the context of teacher training this review-based study examines how AI creates new opportunities through personalized learning experiences, real-time feedback, and classroom simulations that benefit both pre-service and in-service teachers. The study draws upon global and Indian research, policy documents and case studies to highlight AI’s potential in areas such as adaptive learning, virtual simulations, and inclusive education. At the same time, it recognizes challenges such as resistance to technological change within the teaching community. Overall, the findings suggest that AI can make teacher education more dynamic, accessible and effective. The paper concludes with practical recommendations for policymakers, teacher education institutions and researchers to integrate AI in ways that are both sustainable and ethically sound.
Keywords
Artificial Intelligence, Teacher Training, Educational Technology, Pre-Service Education, Personalized Learning, Innovation in Education
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2025, Mandal, S., Pal, C. & Maity, S.K.
Received: October 11, 2025; Revision Received: October 15, 2025; Accepted: October 19, 2025
Article Overview
ISSN 2348-5396
ISSN 2349-3429
18.01.025.20251304
10.25215/1304.025
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Published in Volume 13, Issue 4, October- December, 2025
