Learning Analytics: Fundaments, Applications, and Trends: A View of the Current State of the Art to Enhance e-Learning

Peņa-Ayala, Alejandro (Edited by)

ISBN 10: 3319529765 / ISBN 13: 9783319529769

Editore: Springer, 2017

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303 pages. 9.25x6.25x0.75 inches. In Stock.

Codice articolo x-3319529765

Dati bibliografici

• Titolo: Learning Analytics: Fundaments, Applications, and Trends: A View of the Current State of the Art to Enhance e-Learning
• Editore: Springer
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 3319529765
• ISBN 13: 9783319529769
• Rilegatura: Hardcover
• Condizione: Brand New
• Peso: 0,57 chilogrammi

Descrizione articolo

Riassunto

This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art.

By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.

 

Dalla quarta di copertina

This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art.

By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.