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Synopsis
This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.
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À propos de l?auteur
Myint Swe Khine currently teaches at the School of Education, Curtin University, Australia. He has more than 30 years of experience in teacher education. He received Master's degrees from the University of Southern California, USA, University of Surrey, UK, and the University of Leicester, UK, and a Doctoral degree from Curtin University, Australia. He worked at the National Institute of Education, Nanyang Technological University, Singapore, and was a Professor at Emirates College for Advanced Education in the United Arab Emirates. He has wide-ranging research interests in teacher education, science education, learning sciences, psychometrics, measurement, assessment, and evaluation. He is a member of the Editorial Advisory Board of several international academic journals. Throughout his career, he has published over 40 edited books. The most recent volumes include Methodology for Multilevel Modelling in Education Research: Concepts and Applications (Springer, 2022), and Rhizomatic Metaphor: Legacy of Deleuze and Guattari in Education and Learning (Springer, 2023).
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Machine Learning in Educational Sciences
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on real-world applications of machine learning in educationDiscusses the potential of machine learning for improving education and training processesPromotes ongoing research and the refinement of machine learning methodologies in t. N° de réf. du vendeur 1252897014
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Machine Learning in Educational Sciences
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Springer Nature Singapore, Springer Nature Singapore Feb 2024, 2024
ISBN 10 : 9819993784
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences. 404 pp. Englisch. N° de réf. du vendeur 9789819993789
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Machine Learning in Educational Sciences
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Springer Nature Singapore, Springer Nature Singapore Feb 2024, 2024
ISBN 10 : 9819993784
ISBN 13 : 9789819993789
Neuf
Couverture rigide
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Buch. Etat : Neu. Neuware -This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 404 pp. Englisch. N° de réf. du vendeur 9789819993789
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Machine Learning in Educational Sciences : Approaches, Applications and Advances
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ISBN 13 : 9789819993789
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences. N° de réf. du vendeur 9789819993789
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