Language: English
Published by McGraw-Hill Humanities/Social Sciences/Languages, 2002
ISBN 10: 007282946X ISBN 13: 9780072829464
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Language: English
Published by Taylor & Francis Group, 2020
ISBN 10: 0367136635 ISBN 13: 9780367136635
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Condition: New. pp. 248.
Language: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Language: English
Published by Taylor & Francis Group, 2020
ISBN 10: 0367136635 ISBN 13: 9780367136635
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Language: English
Published by Routledge 2020-12-02, 2020
ISBN 10: 0367136635 ISBN 13: 9780367136635
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Language: English
Published by Routledge 2020-12-02, 2020
ISBN 10: 0367136635 ISBN 13: 9780367136635
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paperback. Condition: Fair. Clean pages with no markings. Some wear on the corners.Ships same day in most cases!The image in this listing is stock photo for reference. Actual item may differ. Any queries, just ask for photos. Your satisfaction matters!
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Add to basketPaperback. Condition: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock.
Language: English
Published by Springer Verlag GmbH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Language: English
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access textbook offers science education researchers a hands-on guide for learning, critically examining, and integrating machine learning (ML) methods into their science education research projects. These methods power many artificial intelligence (AI)-based technologies and are widely adopted in science education research. ML can expand the methodological toolkit of science education researchers and provide novel opportunities to gain insights on science-related learning and teaching processes, however, applying ML poses novel challenges and is not suitable for every research context.The volume first introduces the theoretical underpinnings of ML methods and their connections to methodological commitments in science education research. It then presents exemplar case studies of ML uses in both formal and informal science education settings. These case studies include open-source data, executable programming code, and explanations of the methodological criteria and commitments guiding ML use in each case. The textbook concludes with a discussion of opportunities and potential future directions for ML in science education.This textbook is a valuable resource for science education lecturers, researchers, under-graduate, graduate and postgraduate students seeking new ways to apply ML in their work.
Language: English
Published by Cambridge, Massachusetts: A Bradford Book, The MIIT Press, 2008
ISBN 10: 0262182637 ISBN 13: 9780262182638
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First Edition
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Taschenbuch. Condition: Neu. Applying Machine Learning in Science Education Research | When, How, and Why? | Peter Wulff (u. a.) | Taschenbuch | Springer Texts in Education | xiii | Englisch | 2025 | Springer | EAN 9783031742262 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Language: English
Published by Springer Verlag, Singapore, Singapore, 2024
ISBN 10: 9819953774 ISBN 13: 9789819953776
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Hardcover. Condition: new. Hardcover. This book provides an overview of the various 'Science of Learning' (SoL) research projects led by researchers at the National Institute of Education, Nanyang Technological University, Singapore, and international research collaborators. It presents the goals and rationale behind the Science of Learning in Education (SoLE) initiative and examines a spectrum of topics relevant to bolstering our understanding of the science underlying learning. The Science of Learning (SoL) is an advancing field, with proponents extolling its potential impact on educational practice. This book investigates the possible correlations or causal relationships between brain functioning and development, physiology, environment factors, and their impact on learning. It promotes an interdisciplinary approach to understanding biological to behavioural mechanisms of learning that are oriented toward optimizing and maximizing every learners potential. This book provides an overview of the various 'Science of Learning' (SoL) research projects led by researchers at the National Institute of Education, Nanyang Technological University, Singapore, and international research collaborators. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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