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Lingua: Inglese
Editore: Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Aggiungi al carrelloPaperback. Condizione: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock.
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Editore: Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: 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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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer International Publishing AG, CH, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
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Aggiungi al carrelloPaperback. Condizione: 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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Aggiungi al carrelloTaschenbuch. Condizione: 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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Aggiungi al carrelloTaschenbuch. Condizione: 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.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Da: Revaluation Books, Exeter, Regno Unito
EUR 59,51
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Aggiungi al carrelloPaperback. Condizione: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Springer, Berlin, Springer Nature Switzerland, Peter Wulff, Marcus Kubsch And Christina Krist, Springer, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: 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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EUR 79,15
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 79,55
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Palgrave Macmillan Mär 2025, 2025
ISBN 10: 3031742265 ISBN 13: 9783031742262
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: 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.