Editors:
Includes the latest research on AI in Learning, connecting human learning and machine learning
Provides pedagogical models and practices to use AI at different levels of education and in working-life
Reflects on ethical issues of AI in various contexts
Provides pedagogical models and practices to use AI at different levels of education and in working-life
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Table of contents (20 chapters)
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AI and Ethical Challenges in New Learning Environments
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Back Matter
About this book
AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it.
Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers.Keywords
- Open Access
- artificial intelligence
- life-long learning
- tutoring
- virtual learning
- learning analytics
- well-being
- simulations
- games
- intelligent digital tools
- deep learning
- robotics
- human-machine interaction
Editors and Affiliations
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Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
Hannele Niemi
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Graduate School of Education, Stanford University, Stanford, USA
Roy D. Pea
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Advanced Innovation Center for Future Education, Faculty of Education, Beijing Normal University, Beijing, China
Yu Lu
About the editors
Roy Pea is David Jacks Professor of Education & Learning Sciences at Stanford University, School of Education, and Computer Science (Courtesy), and Director of the H-STAR Institute. His studies and publications in the learning sciences focus on advancing theories, research, tools and social practices of technology-enhanced learning of complex domains, including his role as Co-Director and Co-PI of the NSF-funded LIFE Center, which seeks to develop and test principles about the social foundations of human learning in informal and formal environments with the goal of enhancing human learning from infancy to adulthood. He is also founder and Director of Stanford’s PhD program in Learning Sciences and Technology Design. He is co-author of the 2010 National Education Technology Plan for the US Department of Education, co-editor of Video Research in the Learning Sciences (2007), and co-author of the National Academy of Sciences book: How People Learn (2000). He is a Fellow of the National Academy of Education, Association for Psychological Science, the American Educational Research Association, and the Center for Advanced Study in the Behavioral Sciences. In 2004-2005, Roy was President of the International Society for the Learning Sciences. Roy served from 1999-2009 as a Director for Teachscape, a teacher professional development services company he co-founded with CEO Mark Atkinson.
Lu Yu received the Ph.D. degree from National University of Singapore in computer engineering, and B.S./M.S. degrees from Beijing University of Aeronautics and Astronautics (Beihang University). He is currently an Associate Professor with the School of Educational Technology, Faculty of Education, Beijing Normal University (BNU), where he also serves as the director of the artificial intelligence lab at the advanced innovation center for future education (AICFE). He has published more than 40 academic papers in the prestigious journals and conferences (e.g., IEEE TKDE, TMC, ICDM, AIED, CIKM, EDBT, IJCAI, ICDE), and currently serves as the PC member for multiple international conferences (e.g., AAAI, AIED, CIKM). Before joining BNU, he was a research scientist and principle investigator at the Institute for Infocomm Research (I2R), A*STAR, Singapore. His research interests are Learner Modeling, Robotics for Education, Intelligent Tutoring System, Educational Data Mining, Data Analytics and Ubiquitous Computing
Bibliographic Information
Book Title: AI in Learning: Designing the Future
Editors: Hannele Niemi, Roy D. Pea, Yu Lu
DOI: https://doi.org/10.1007/978-3-031-09687-7
Publisher: Springer Cham
eBook Packages: Behavioral Science and Psychology, Behavioral Science and Psychology (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
License: CC BY
Hardcover ISBN: 978-3-031-09686-0Published: 28 November 2022
Softcover ISBN: 978-3-031-09689-1Published: 28 November 2022
eBook ISBN: 978-3-031-09687-7Published: 26 November 2022
Edition Number: 1
Number of Pages: XXV, 344
Number of Illustrations: 7 b/w illustrations, 42 illustrations in colour
Topics: Behavioral Sciences and Psychology, Computer Application in Social and Behavioral Sciences, Education, Cognitive Science, Pedagogy, Artificial Intelligence