Recommender Systems for Learning

by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Erik Duval

Overview

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Product Details

ISBN-13:	9781461443612
Publisher:	Springer-Verlag New York, LLC
Publication date:	08/28/2012
Series:	SpringerBriefs in Electrical and Computer Engineering
Sold by:	Barnes & Noble
Format:	eBook
Pages:	76
File size:	479 KB

Table of Contents

Introduction and Background.- TEL as a recommendation context.- Survey and Analysis of TEL Recommender Systems.- Challenges and Outlook.