Adoption of Data Analytics in Higher Education Learning and Teaching - Couverture rigide

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9783030473914: Adoption of Data Analytics in Higher Education Learning and Teaching

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ISBN 10 : 3030473910 ISBN 13 : 9783030473914

Editeur : Springer Nature Switzerland AG, 2020

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Part I. Theoretical Foundations and Frameworks.- Part II. Technological Infrastructure and Staff Requirements.- Part III. Institutional Governance and Policy Implementation.- Part IV. Case Studies.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer Nature Switzerland AG
Date d'�dition: 2020
Langue: anglais
ISBN 10: 3030473910
ISBN 13: 9783030473914
Reliure: Reli�
Nombre de pages: 472
�diteur: Ifenthaler Dirk, Gibson David
Coordonn�es du fabricant: ProductSafety@springernature.com
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Allemagne

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Adoption of Data Analytics in Higher Education Learning and Teaching (eng)

Ifenthaler, Dirk

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Adoption of Data Analytics in Higher Education Learning and Teaching (Advances in Analytics for Learning and Teaching)

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Adoption of Data Analytics in Higher Education Learning and Teaching

Ifenthaler, Dirk|Gibson, David

Edit� par Springer International Publishing, 2020

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides insights into how higher education institutions adopt learning analytics and data mining studiesContributions from distinguished international researchersConsiders theoretical perspectives, innovative technol. N� de r�f. du vendeur 448682936

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Adoption of Data Analytics in Higher Education Learning and Teaching

David Gibson

Edit� par Springer International Publishing, Springer Nature Switzerland Aug 2020, 2020

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.This volumeprovides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education. 472 pp. Englisch. N� de r�f. du vendeur 9783030473914

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Adoption of Data Analytics in Higher Education Learning and Teaching (Advances in Analytics for Learning and Teaching)

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Adoption of Data Analytics in Higher Education Learning and Teaching

David Gibson

Edit� par Springer International Publishing, Springer International Publishing Aug 2020, 2020

ISBN 10 : 3030473910 ISBN 13 : 9783030473914

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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 472 pp. Englisch. N� de r�f. du vendeur 9783030473914

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Adoption of Data Analytics in Higher Education Learning and Teaching

David Gibson

Edit� par Springer International Publishing, Springer Nature Switzerland, 2020

ISBN 10 : 3030473910 ISBN 13 : 9783030473914

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.This volumeprovides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education. N� de r�f. du vendeur 9783030473914

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