Handbook of Generative AI in Education

Integrating Research into Practice

Generative AI is transforming educational systems at a pace that challenges researchers, practitioners, and institutions to develop principled approaches to understanding, evaluating, and implementing these technologies responsibly. In response to this need, this volume synthesizes research on the use of Generative Artificial Intelligence (GAI) in education from leading global scholars across disciplines. The book explores effective methodologies and frameworks for advancing research and applications of GAI in higher education and related domains while addressing new possibilities for both the research and application of teaching, learning, and assessment. It examines the ways in which GAI can be used to transform education within the context of risks, ethical concerns, and other potential negative impacts, addressing the significant new challenges GAI may pose for instructors, students, administrators and researchers.

Key areas of coverage include:

•    Foundational frameworks for understanding GAI systems and their implications for educational research and practice
•    Empirical evaluation of AI tutors, agentic systems, and automated feedback against rigorous learning science standards
•    Innovations in assessment that expand what can be measured and at what scale
•    Applications and findings across K–12, higher education, health sciences, and workforce training, with attention to equity and institutional implementation
•    Ethical implications of GAI use in educational research and applications

The Handbook of Generative AI in Education is an essential resource for researchers, professors, educators, and graduate students as well as professionals and practitioners in instructional design, educational technology, educational psychology, health science education, teacher education, and educational practice and policy.

Contributor: Michael C. Mayrath (Edited by), John T. Behrens (Edited by), Daniel H. Robinson (Edited by)

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