Chapter 20

Handbook of Learning Analytics
First Edition

Applying Recommender Systems
for Learning Analytics: A Tutorial

Soude Fazeli, Hendrik Drachsler & Peter Sloep


Abstract

This chapter provides an example of how a recommender system experiment can be conducted in the domain of learning analytics (LA). The example study presented in this chapter followed a standard methodology for evaluating recommender systems in learning. The example is set in the context of the FP7 Open Discovery Space (ODS) project that aims to provide educational stakeholders in Europe with a social learning platform in a social network similar to Facebook, but unlike Facebook, exclusively for learning and knowledge sharing. In this chapter, we describe a full recommender system data study in a stepwise process. Furthermore, we outline shortcomings for data-driven studies in the domain of learning and emphasize the high need for an open learning analytics platform as suggested by the SoLAR society.

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About this Chapter

Title
Applying Recommender Systems
for Learning Analytics: A Tutorial

Book Title
Handbook of Learning Analytics

Pages
pp. 235-240

Copyright
2017

DOI
10.18608/hla17.020

ISBN
978-0-9952408-0-3

Publisher
Society for Learning Analytics Research

Authors
Soude Fazeli1
Hendrik Drachsler2
Peter Sloep2

Author Affiliations
1. Welten Institute, Research Centre for Learning, Teaching and Technology, The Netherlands
2. Open University of the Netherlands, The Netherlands

Editors
Charles Lang3
George Siemens4
Alyssa Wise5
Dragan Gašević6

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

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