Chapter 10

Handbook of Learning Analytics
First Edition

Emotional Learning Analytics

Sidney K. D’Mello


Abstract

This chapter discusses the ubiquity and importance of emotion to learning. It argues that substantial progress can be made by coupling the discovery-oriented, data-driven, analytic methods of learning analytics (LA) and educational data mining (EDM) with theoretical advances and methodologies from the affective and learning sciences. Core, emerging, and future themes of research at the intersection of these areas are discussed.

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About this Chapter

Title
Emotional Learning Analytics

Book Title
Handbook of Learning Analytics

Pages
pp. 115-127

Copyright
2017

DOI
10.18608/hla17.010

ISBN
978-0-9952408-0-3

Publisher
Society for Learning Analytics Research

Authors
Sidney K. D’Mello

Author Affiliations
Departments of Psychology and Computer Science & Engineering, University of Notre Dame, USA

Editors
Charles Lang1
George Siemens2
Alyssa Wise3
Dragan Gašević4

Editor Affiliations
1. Teachers College, Columbia University, USA
2. LINK Research Lab, University of Texas at Arlington, USA
3. Learning Analytics Research Network, New York University, USA
4. Schools of Education and Informatics, University of Edinburgh, UK

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