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Recommender systems for learning / / Nikos Manouselis ... [et al.]



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Titolo: Recommender systems for learning / / Nikos Manouselis ... [et al.] Visualizza cluster
Pubblicazione: New York, : Springer, c2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (84 p.)
Disciplina: 006.33
Soggetto topico: Educational technology
Recommender systems (Information filtering)
Altri autori: ManouselisNikos  
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Introduction and Background -- TEL as a recommendation context -- Survey and Analysis of TEL Recommender Systems -- Challenges and Outlook.
Sommario/riassunto: 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.
Titolo autorizzato: Recommender Systems for Learning  Visualizza cluster
ISBN: 1-283-61174-0
9786613924193
1-4614-4361-X
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910437922803321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: SpringerBriefs in Electrical and Computer Engineering, . 2191-8112