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Bücher Englische Bücher Wissen & Bildung Geisteswissenschaft, Kunst, Musik Pädagogik Erwachsenenbildung Applying Machine Learning in Science Education Research
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Applying Machine Learning in Science Education Research
(Broschiert, Englisch)
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Beschreibung
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. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
01.03.2025
Sprache
Englisch
EAN
9783031742262
Herausgeber
Springer International Publishing
Serien- oder Bandtitel
Springer Texts in Education
Sonderedition
Nein
Seitenanzahl
369
Auflage
1
Einbandart
Broschiert
Buch Untertitel
When, How, and Why?
Schlagwörter
Open Access, Machine learning, Natural language processing, science education research, supervised and unsupervised learning, Probabilistic modeling, artificial intelligence in Science education, Machine learning models, Human-machine interactions, Pattern recognition, computational grounded theory, reinforcement learning, deep neural networks, multimodal learning, transfer learning, qualitative and quantitative research methods, computer-aided tutoring, human-machine interaction, big data, complex systems theory
Thema-Inhalt
JNU - Fachspezifischer Unterricht
PD - Naturwissenschaften, allgemein
JNZ - Lerntechniken
UYQM - Maschinelles Lernen
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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