Handbook of Generative AI in Education: Integrating Research into Practice - Tapa dura

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Michael Mayrath, Ph.D., is a Senior Research Fellow at Ponce Health Sciences University (PHSU) and the President of Tiber Health Innovation (THI), an educational technology company. THI works with universities and organizations in the U.S. and beyond to utilize AI and analytics for teaching, learning, and assessment. THI supports PHSU's MD and health science programs with an AI tutoring platform and predictive analytics for the USMLE Step 1. Dr. Mayrath has launched innovative undergraduate and graduate degree programs around the world, ranging from Kenya to Guyana to Malaysia. He has published numerous peer-reviewed articles, including publications in top medical education journals such as AAMC's Academic Medicine. He was the lead editor of the book Technology-Based Assessments for 21st Century Skills. Dr. Mayrath received his Ph.D. in educational psychology from the University of Texas at Austin and subsequently worked as a postdoctoral fellow at Harvard University. His professional mission for more than 25 years has been to increase student outcomes and empower educators by combining innovative technologies with educational psychology research.

John T. Behrens, Ph.D., is a Professor of the Practice and Director of the Technology & Digital Studies Program, and Concurrent Professor of the Practice in the Department of Computer Science and Engineering at the University of Notre Dame where he also serves as Director of the Office of Digital Strategy in the College of Arts & Letters.  Dr. Behrens has more than 20 years of industry experience developing globally deployed intelligent software systems to advance learning and assessment. He has published widely in areas of learning science, data science (including artificial intelligence), educational assessment and measurement, and the enhancement of learning and assessment systems with these technologies. Prior to entering industry, he was a tenured Associate Professor of Psychology in Education at Arizona State University focused on improving learning systems with statistical and measurement methods. His research interests include the impact of users’ mental models of intelligent systems on their interactions, system transparency and explanability, social impacts of AI, and the application of AI methods to learning and research systems development.

Daniel H. Robinson, Ph.D., M.Ed., is a professor in the College of Education at the University of Texas at Arlington. He previously served as Associate Dean of Research and Chair of the Department of Curriculum and Instruction at UTA, and Director of the School of Education at Colorado State University. Dr. Robinson serves as Specialty Chief Editor of Frontiers in Psychology: Educational Psychology and has previously served as Editor of Educational Psychology Review and as Associate Editor of the Journal of Educational Psychology. He has also served as an editorial board member of nine refereed international journals. Dr. Robinson has published more than 100 articles, books, and book chapters, presented more than 100 papers at research conferences, and taught more than 100 college courses. His research interests include educational technology innovations and team-based approaches that may facilitate learning. He was a Visiting Fulbright Scholar at Victoria University, Wellington, New Zealand (2011), and was named as one of the most published authors in educational psychology journals from 1991-2002, 2003-2008, and 2009-2014, Contemporary Educational Psychology, 2004, 2010, 2015.

De la contraportada

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.