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http://localhost:8080/xmlui/handle/123456789/164Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Gupta, Adit | - |
| dc.date.accessioned | 2026-06-29T13:20:27Z | - |
| dc.date.available | 2026-06-29T13:20:27Z | - |
| dc.date.issued | 2026-06-28 | - |
| dc.identifier.isbn | 978-81-952808-3-4 | - |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/164 | - |
| dc.description | This guide was written for teacher educators and pre-service teachers who want to engage with artificial intelligence practically and purposefully, without the jargon, the hype, or the assumption that everyone is starting from the same place. Organised around the real stages of pre-service teacher preparation in India, it moves from lesson planning and micro-teaching through school internship, assessment redesign, multilingual classrooms, and institutional getting-started strategies. Every chapter is grounded in the realities of B.Ed. and ITEP programmes across Indian cities, towns, and districts, and every chapter ends with one concrete action the reader can take immediately, no budget, no institutional approval, and no technical expertise required. At the heart of the guide is the AI Interaction Knowledge framework, which proposes four practical competencies for working effectively and critically with AI, and the Continuous and Comprehensive Evaluation model, both developed through research and practice at MIER College of Education, Jammu. This is not a guide about what AI might do for education someday. It is a guide about what teacher educators and student teachers can do with AI right now, on Monday morning, in the classrooms and institutions they already work in. | en_US |
| dc.description.abstract | Artificial intelligence is reshaping education faster than most teacher education institutions have been able to respond. This guide offers a practical, jargon-free resource for teacher educators and pre-service teachers navigating that change. Organised around the stages of pre-service teacher preparation, it covers lesson planning, micro-teaching, school internship, assessment redesign, multilingual classrooms, ethics, and institutional getting-started strategies. Grounded in the AI Interaction Knowledge (AIK) framework and the Continuous and Comprehensive Evaluation (C²E) model developed at MIER College of Education, Jammu, every chapter concludes with one concrete action the reader can take immediately. This guide was written for the Monday morning classroom, not the conference hall. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | MIER College of Education (Autonomous) | en_US |
| dc.subject | AI in Teacher Education | en_US |
| dc.subject | Teacher Education | en_US |
| dc.subject | Teacher Educators | en_US |
| dc.subject | Teacher Trainees | en_US |
| dc.title | AI in the Classroom Before the Classroom: A Practitioner's Guide for Teacher Educators and Pre-Service Teachers in India | en_US |
| dc.type | Book | en_US |
| Appears in Collections: | MCE e-Books | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| AI Teacher Education Practical Guide.pdf | This guide was written for teacher educators and pre-service teachers who want to engage with artificial intelligence practically and purposefully, without the jargon, the hype, or the assumption that everyone is starting from the same place. Organised around the real stages of pre-service teacher preparation in India, it moves from lesson planning and micro-teaching through school internship, assessment redesign, multilingual classrooms, and institutional getting-started strategies. Every chapter is grounded in the realities of B.Ed. and ITEP programmes across Indian cities, towns, and districts, and every chapter ends with one concrete action the reader can take immediately, no budget, no institutional approval, and no technical expertise required. At the heart of the guide is the AI Interaction Knowledge framework, which proposes four practical competencies for working effectively and critically with AI, and the Continuous and Comprehensive Evaluation model, both developed through research and practice at MIER College of Education, Jammu. This is not a guide about what AI might do for education someday. It is a guide about what teacher educators and student teachers can do with AI right now, on Monday morning, in the classrooms and institutions they already work in. | 2.49 MB | Adobe PDF | View/Open |
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