TY  - BOOK
AU  - Manouselis,Nikos
AU  - Drachsler,Hendrik
AU  - Verbert,Katrien
AU  - Duval,Erik
ED  - SpringerLink (Online service)
TI  - Recommender Systems for Learning
T2  - SpringerBriefs in Electrical and Computer Engineering,
SN  - 9781461443612
AV  - QA75.5-76.95 
U1  - 005.7 23
PY  - 2013///
CY  - New York, NY
PB  - Springer New York, Imprint: Springer
KW  - Computer science
KW  - Computers
KW  - Education
KW  - Computer Science
KW  - Information Systems and Communication Service
KW  - Education, general
N1  - Introduction and Background -- TEL as a recommendation context -- Survey and Analysis of TEL Recommender Systems -- Challenges and Outlook
N2  - 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
UR  - http://dx.doi.org/10.1007/978-1-4614-4361-2
ER  -