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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationLanguage: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. 2025 ed.
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Applying Machine Learning in Science Education Research: When, how, and why? (Springer Texts in Education)
Book 57 of 57: Springer Texts in EducationUS$ 55.65
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Applying Machine Learning in Science Education Research : When, How and Why?
Book 57 of 57: Springer Texts in EducationSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Applying Machine Learning in Science Education Research: When, How, and Why? (Springer Texts in Education)
Book 57 of 57: Springer Texts in EducationSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Applying Machine Learning in Science Education Research : When, How and Why?
Book 57 of 57: Springer Texts in EducationSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Applying Machine Learning in Science Education Research: When, How and Why?
Book 57 of 57: Springer Texts in EducationUS$ 100.80
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Add to basketPaperback. Condition: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationLanguage: English
Published by Springer Verlag GmbH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Condition: New.
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Applying Machine Learning in Science Education Research : When, How, and Why?
Language: English
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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.
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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.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationLanguage: English
Published by Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
US$ 65.37
US$ 87.36 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: New. 2025 ed. 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.
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Lehrkräftebildung neu gedacht : Ein Praxishandbuch für die Lehre in den Naturwissenschaften und deren Didaktiken
Language: German
Published by Waxmann Verlag Jun 2021, 2021
ISBN 10: 3830943490 ISBN 13: 9783830943495
Taschenbuch. Condition: Neu. Neuware - Die Lehrkräftebildung in den Naturwissenschaften hat die Aufgabe, die angehenden Lehrkräfte der Biologie, Chemie und Physik auf die Gestaltung des Unterrichts der Zukunft vorzubereiten. Dabei wurden in den letzten Jahren verstärkt neue Lehr-Lern-Formate, Technologien und Methoden an einzelnen Hochschulstandorten entwickelt, um dieser Herausforderung gerecht zu werden. Dieses Buch gibt einen praxisbezogenen Einblick in Innovationen der Lehrkräftebildung in den Naturwissenschaften und macht sie damit auch für den Einsatz an weiteren deutschsprachigen Hochschulen zugänglich. Dazu präsentieren die Autorinnen und Autoren von über 30 Hochschulen in Deutschland, Österreich und der Schweiz neue Ansätze zu Unterstützungsmöglichkeiten der Kompetenzentwicklung, zum Einsatz von Medien und zur Förderung der Planung und Reflexion von Unterricht. Unterstützt wird dies durch umfassende Onlinematerialien, was die Nutzung an anderen Hochschulstandorten begünstigen und damit die Weiterentwicklung der Lehrkräftebildung in den Naturwissenschaften insgesamt fördern soll.
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Taschenbuch. Condition: Neu. Lehrkräftebildung neu gedacht | Ein Praxishandbuch für die Lehre in den Naturwissenschaften und deren Didaktiken | Marcus Kubsch | Taschenbuch | 268 S. | Deutsch | 2021 | Waxmann Verlag | EAN 9783830943495 | Verantwortliche Person für die EU: Waxmann Verlag GmbH, Steinfurter Str. 555, 48159 Münster, info[at]waxmann[dot]com | Anbieter: preigu.
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Condition: new. Questo è un articolo print on demand.
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Applying Machine Learning in Science Education Research: When, How and Why?
Book 57 of 57: Springer Texts in EducationUS$ 69.08
US$ 16.80 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock. This item is printed on demand.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationLanguage: English
Published by Springer, Berlin, Springer Nature Switzerland, Peter Wulff, Marcus Kubsch And Christina Krist, Springer, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 369 pp. Englisch.
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Applying Machine Learning in Science Education Research
Book 57 of 57: Springer Texts in EducationLanguage: English
Published by Springer, Palgrave Macmillan Mär 2025, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 384 pp. Englisch.
