Machine Learning Paradigms

Advances in Learning Analytics

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Reference & Language, Education & Teaching, Educational Theory, Educational Psychology, General Computing
Cover of the book Machine Learning Paradigms by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783030137434
Publisher: Springer International Publishing Publication: March 16, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783030137434
Publisher: Springer International Publishing
Publication: March 16, 2019
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Kautilya and Non-Western IR Theory by
Cover of the book Land Use Competition by
Cover of the book Humanizing Mathematics and its Philosophy by
Cover of the book Cognitive Communication and Cooperative HetNet Coexistence by
Cover of the book Sexual Violence by
Cover of the book PEGIDA and New Right-Wing Populism in Germany by
Cover of the book The Financial Crisis by
Cover of the book Numerical Methods for Nonlinear Partial Differential Equations by
Cover of the book Financing Basic Income by
Cover of the book Manipulation of Allelopathic Crops for Weed Control by
Cover of the book Climate Gradients and Biodiversity in Mountains of Italy by
Cover of the book Information Security Applications by
Cover of the book Float Glass Innovation in the Flat Glass Industry by
Cover of the book Varying Gravity by
Cover of the book Algorithmic Aspects of Cloud Computing by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy