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This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the…mehr
This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.
Shengquan Yu received his Ph.D. in Educational Technology from Beijing Normal University (BNU). He is currently a Professor at BNU, and serves as executive director of the Advanced Innovation Center for Future Education, as well as the director of the Joint Laboratory for Mobile Learning, funded by the Ministry of Education and China Mobile Communications Corporation. His research interests mainly lie in mobile education and ubiquitous learning, key technologies for online learning platforms, regional education, informationization, education and big data, information technology and curriculum integration. Yu Lu received his Ph.D. in Computer Engineering from the National University of Singapore. He is currently an Associate Professor at the Faculty of Education, Beijing Normal University (BNU), where he also serves as director of the artificial intelligence lab at the advanced innovation center for future education. He has published more than 50 academic papers in prominent journals and conference proceedings. Before joining BNU, he was a research scientist and principle investigator at the Institute for Infocomm Research (I2R), A*STAR, Singapore. His current research interests lie at the intersection of artificial intelligence and educational technology.
Inhaltsangabe
Chapter 1: Background.- Chapter 2: Basics of Artificial Intelligence.- Chapter 3: Intelligent Education Environment.- Chapter 4: Intelligent Learning Process Support.- Chapter 5: Intelligent Teacher Assistant.- Chapter 6: Intelligent Education Assessment.- Chapter 7: Intelligent Education Management and Service.- Chapter 8: Frontiers and Future of AI in Education.
Chapter 1: Background.- Chapter 2: Basics of Artificial Intelligence.- Chapter 3: Intelligent Education Environment.- Chapter 4: Intelligent Learning Process Support.- Chapter 5: Intelligent Teacher Assistant.- Chapter 6: Intelligent Education Assessment.- Chapter 7: Intelligent Education Management and Service.- Chapter 8: Frontiers and Future of AI in Education.