Machine Learning Paradigms

Lieferzeit: Lieferbar innerhalb 14 Tagen

160,49 

Advances in Learning Analytics, Intelligent Systems Reference Library 158

ISBN: 3030137422
ISBN 13: 9783030137427
Herausgeber: Maria Virvou/Efthimios Alepis/George A Tsihrintzis et al
Verlag: Springer Verlag GmbH
Umfang: xvi, 223 S., 31 s/w Illustr., 29 farbige Illustr., 223 p. 60 illus., 29 illus. in color.
Erscheinungsdatum: 26.03.2019
Auflage: 1/2020
Produktform: Gebunden/Hardback
Einband: Gebunden

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators‘ and learners‘ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:- Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation;- Using learning analytics to predict student performance;- Using learning analytics to create learning materials and educational courses; and- Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning.The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Artikelnummer: 6255494 Kategorie:

Beschreibung

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators' and learners' data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:- Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation;- Using learning analytics to predict student performance;- Using learning analytics to create learning materials and educational courses; and- Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Herstellerkennzeichnung:


Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

Das könnte Ihnen auch gefallen …