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  • Book
  • Open Access
  • © 2023

AI in Learning: Designing the Future

  • 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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Softcover Book USD 49.99
Price excludes VAT (USA)
Hardcover Book USD 59.99
Price excludes VAT (USA)

Table of contents (20 chapters)

  1. Front Matter

    Pages i-xxv
  2. Introduction to AI in Learning: Designing the Future

    • Hannele Niemi, Roy D. Pea, Yu Lu
    Pages 1-15Open Access
  3. AI Expanding Learning and Wellbeing Throughout Life

    1. Front Matter

      Pages 17-17
    2. Assessing and Tracking Students’ Wellbeing Through an Automated Scoring System: School Day Wellbeing Model

      • Xin Tang, Katja Upadyaya, Hiroyuki Toyama, Mika Kasanen, Katariina Salmela-Aro
      Pages 55-71Open Access
    3. Learning from Intelligent Social Agents as Social and Intellectual Mirrors

      • Bethanie Maples, Roy D. Pea, David Markowitz
      Pages 73-89Open Access
    4. Analysis and Improvement of Classroom Teaching Based on Artificial Intelligence

      • Zhong Sun, Zi Chun Yu, Fei Yun Xu
      Pages 105-121Open Access
  4. AI in Games and Simulations

    1. Front Matter

      Pages 123-123
    2. Learning Clinical Reasoning Through Gaming in Nursing Education: Future Scenarios of Game Metrics and Artificial Intelligence

      • Jaana-Maija Koivisto, Sara Havola, Henna Mäkinen, Elina Haavisto
      Pages 159-173Open Access
    3. AI-Supported Simulation-Based Learning: Learners’ Emotional Experiences and Self-Regulation in Challenging Situations

      • Heli Ruokamo, Marjaana Kangas, Hanna Vuojärvi, Liping Sun, Pekka Qvist
      Pages 175-192Open Access
  5. AI Technologies for Education andIntelligent Tutoring Systems

    1. Front Matter

      Pages 193-193
    2. Training Hard Skills in Virtual Reality: Developing a Theoretical Framework for AI-Based Immersive Learning

      • Tiina Korhonen, Timo Lindqvist, Joakim Laine, Kai Hakkarainen
      Pages 195-213Open Access
    3. Multiple Users’ Experiences of an AI-Aided Educational Platform for Teaching and Learning

      • Shuanghong Jenny Niu, Xiaoqing Li, Jiutong Luo
      Pages 215-231Open Access
    4. Deep Learning in Automatic Math Word Problem Solvers

      • Dongxiang Zhang
      Pages 233-246Open Access
    5. Recent Advances in Intelligent Textbooks for Better Learning

      • Bo Jiang, Meijun Gu, Ying Du
      Pages 247-261Open Access
  6. AI and Ethical Challenges in New Learning Environments

    1. Front Matter

      Pages 263-263

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

  • Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland

    Hannele Niemi

  • Graduate School of Education, Stanford University, Stanford, USA

    Roy D. Pea

  • Advanced Innovation Center for Future Education, Faculty of Education, Beijing Normal University, Beijing, China

    Yu Lu

About the editors

Hannele Niemi is Professor, Research Director at the University of Helsinki and been she has nominated as UNESCO Chair on Educational Ecosystems for Equity and Quality of Learning 2018-. She is also the Chair of The University Board at the University of Lapland (2018-). She served as Vice-Rector at the University of Helsinki (2003—2009). She have invited as honorary doctor of professor in 5 universities. She leads Finnish national research consortium AI in Learning (2020-2021) that has active cooperation with researchers, companies and practitioners seeking new solutions how AI can support human learning. The project  has  also a wide cooperation in China and U.S.A.  She has invited as an expert in tens of countries and has over 400 publications on teaching, learning, teacher education, and technology-supported learning environments.  Niemi has been a scientific leader for several large national research projects in Finland, including the Finnable 2020 (finnable.fi) program for advancing educational technology and 21st century skills in schools (2012-2015). She also served as Director of the national research program "Life as Learning", which was supported by the Academy of Finland (2002-2006). She has been a member of a Steering Committee of the British National Research Programme (the Teaching and Learning Research Programme [TLRP]; 2003-2008). She currently serves as an advisor and reviewer for several scientific journals. She has served as a member of several scientific councils, including the European Science Foundation, the Academy of Finland, and the University of Helsinki and worked as a reviewer for research councils in many countries, including Norway, Portugal, Estonia, and Singapore. She has been invited as a panel member or chair of the research evaluations of educational sciences in many universities and invited as a panel member for the evaluations of the quality and effectiveness of more than 10 universities in Europe (2005-2020) and also in evaluations of 3 European evaluation councils in Higher Education.

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

Buying options

Softcover Book USD 49.99
Price excludes VAT (USA)
Hardcover Book USD 59.99
Price excludes VAT (USA)