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Recommender Systems for Learning (Springerbriefs in Electrical and Computer Engineering)

Recommender Systems for Learning (Springerbriefs in Electrical and Computer Engineering) Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

1

Table of Contents

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

Product Details

ISBN:
9781461443605
Publisher:
Springer
Subject:
Online Services - General
Author:
Drachsler, Hendrik
Author:
Manouselis, Nikos
Author:
Verbert, Katrien
Author:
Duval, Erik
Subject:
recommender systems
Subject:
TEL datasets
Subject:
Personalization
Subject:
recommendation algorithms
Subject:
technology enhanced learning (TEL)
Subject:
Information Systems and Communication Service
Subject:
Education-General
Copyright:
Edition Description:
2012
Series:
SpringerBriefs in Electrical and Computer Engineering
Publication Date:
20120701
Binding:
TRADE PAPER
Language:
English
Pages:
87
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Internet » Online
Education » General
History and Social Science » Politics » General

Recommender Systems for Learning (Springerbriefs in Electrical and Computer Engineering)
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Product details 87 pages Springer - English 9781461443605 Reviews:
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