Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

Teaching and Learning in the Age of Generative AI explores how educators can effectively harness the potential of artificial intelligence technologies while skillfully navigating its pedagogical, technical, ethical, institutional, and societal implications. The increasing accessibility of AI technologies among K-12 and higher education students has raised extensive concerns around academic integrity, though a deeper lineage of research and development suggests that these tools may be used to supplement instruction, prioritize critical thinking, and promote digital literacy. Bookended by in-depth analyses of the historical and future trajectories of artificial intelligence in education, this comprehensive resource provides evidence-based strategies for classroom implementation and helpful summaries of common benefits and risks. Teaching assistance, personalized learning, redefined assessments, anti-bias measures, and safeguards against misconduct and privacy infringement are among the wealth of topics addressed in these chapters. This book is an ideal text for undergraduate and graduate students of teacher education and curriculum and instruction as well as for higher education teaching faculty, school technology coordinators, and talent development personnel in training and in service.

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Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

Teaching and Learning in the Age of Generative AI explores how educators can effectively harness the potential of artificial intelligence technologies while skillfully navigating its pedagogical, technical, ethical, institutional, and societal implications. The increasing accessibility of AI technologies among K-12 and higher education students has raised extensive concerns around academic integrity, though a deeper lineage of research and development suggests that these tools may be used to supplement instruction, prioritize critical thinking, and promote digital literacy. Bookended by in-depth analyses of the historical and future trajectories of artificial intelligence in education, this comprehensive resource provides evidence-based strategies for classroom implementation and helpful summaries of common benefits and risks. Teaching assistance, personalized learning, redefined assessments, anti-bias measures, and safeguards against misconduct and privacy infringement are among the wealth of topics addressed in these chapters. This book is an ideal text for undergraduate and graduate students of teacher education and curriculum and instruction as well as for higher education teaching faculty, school technology coordinators, and talent development personnel in training and in service.

56.99 In Stock
Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

Teaching and Learning in the Age of Generative AI: Evidence-Based Approaches to Pedagogy, Ethics, and Beyond

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Overview

Teaching and Learning in the Age of Generative AI explores how educators can effectively harness the potential of artificial intelligence technologies while skillfully navigating its pedagogical, technical, ethical, institutional, and societal implications. The increasing accessibility of AI technologies among K-12 and higher education students has raised extensive concerns around academic integrity, though a deeper lineage of research and development suggests that these tools may be used to supplement instruction, prioritize critical thinking, and promote digital literacy. Bookended by in-depth analyses of the historical and future trajectories of artificial intelligence in education, this comprehensive resource provides evidence-based strategies for classroom implementation and helpful summaries of common benefits and risks. Teaching assistance, personalized learning, redefined assessments, anti-bias measures, and safeguards against misconduct and privacy infringement are among the wealth of topics addressed in these chapters. This book is an ideal text for undergraduate and graduate students of teacher education and curriculum and instruction as well as for higher education teaching faculty, school technology coordinators, and talent development personnel in training and in service.


Product Details

ISBN-13: 9781040335574
Publisher: Taylor & Francis
Publication date: 04/30/2025
Sold by: Barnes & Noble
Format: eBook
Pages: 436
File size: 7 MB

About the Author

Joseph Rene Corbeil is Professor of Educational Technology at The University of Texas Rio Grande Valley, USA.

Maria Elena Corbeil is Professor of Educational Technology at The University of Texas Rio Grande Valley, USA.

Table of Contents

Part I. Foundations and Frameworks of AI in Education 1. What is Generative AI? A Primer 2. Developing a Framework for Implementing AI in Education and Evaluating Its Use Part II. Transformative Teaching and Learning with AI 3. Transformative Teaching with AI 4. The Age of Chat: Education and the Rise of No-Code Chatbots 5. Promoting Critical Thinking and Problem-Solving Through AI Part III. Ethical and Institutional Considerations 6. Rethinking Cheating in the Age of AI 7. Developing Institutional Policies for AI in Education 8. Navigating Risks: Inaccuracies, Bias, Disinformation, and Privacy in Educational AI 9. Exploring the Generative Artificial Intelligence Fair Use Policy Landscape in Higher Education Part IV. Preparing Educators and Students for AI Integration 10. Teaching Generative AI in Higher Education: Strategies, Implications, and Reflective Practices 11. Preparing Pre-Service and In-Service Teachers for the AI-Driven Classroom 12. Preparing Students to Live and Work in an AI-Driven World: Ideas for Educators and Students Part V. Future Trends and Implications of AI in Education 13. Redefining Assessments in the Age of AI 14. AI and the Digital Divide 15. Defining Key Workplace Competencies in the AI Era: A Framework for AI-Powered Education 16. AI-Driven Self-Directed Lifelong Learning: Personalization and Empowerment in the Digital Age 17. The Future of Learning: AI-Driven Education in 2040

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