Artificial Intelligence and the Future of Teacher Education: Pedagogical Innovations, Professional Competence, and Ethical Challenges
Authors-Dr G. Kokila Selva Kumari
Keyword-artificial intelligence, teacher education, generative AI, AI literacy, teacher professional develop-ment, pedagogical innovation, educational ethics
Artificial intelligence (AI) is increasingly influencing educational practices, creating new possi-bilities and challenges for teacher education. Its applications extend beyond automated content generation to lesson planning, instructional design, assessment, personalised learning, reflective practice, and professional development. These developments require teacher education institu-tions to reconsider how prospective and practising teachers acquire pedagogical knowledge, exercise professional judgement, and prepare learners for an AI-mediated educational environ-ment. This article examines the implications of AI for teacher education through a thematic syn-thesis of published research and policy frameworks. The discussion is organised around five interconnected themes that examine the role of artificial intelligence in shaping the future of teacher education. These include the use of AI to support pedagogical innovation and improve instructional practices; the development of AI competence among prospective and practising teachers; the changing nature of assessment, feedback, and professional learning; the ethical, epistemological, and institutional challenges associated with AI adoption; and the strategies required to integrate AI responsibly into teacher education programmes. Together, these themes provide a basis for understanding how AI can enhance teaching and learning while addressing the professional, ethical, and institutional considerations necessary for its effective implementa-tion. Research reviews indicate that AI can support instructional planning, feedback, resource development, and professional learning, although the strength and sustainability of these benefits depend on the design of learning activities and the preparation of teachers. Concerns relating to inaccurate outputs, algorithmic bias, privacy, academic integrity, unequal access, and overde-pendence on automated systems remain important. The article argues that active AI integration requires more than technical familiarity. Teacher education should develop the capacity to evalu-ate AI-generated information, design pedagogically appropriate learning experiences, protect learner interests, and retain human responsibility for educational decisions. It proposes a human-centred framework for integrating AI literacy, pedagogical competence, ethical judgement, reflec-tive practice, and institutional support into teacher preparation. The article concludes that AI should strengthen teachers' professional capacity rather than diminish their agency, relationships with learners, or responsibility for educational quality.
Doi-[https://doi.org/10.5281/zenodo.23336496]