PLEM a Web 2.0 driven Long Tail aggregator and filter for elearning
Identifieur interne : 000243 ( France/Analysis ); précédent : 000242; suivant : 000244PLEM a Web 2.0 driven Long Tail aggregator and filter for elearning
Auteurs : Mohamed Amine Chatti [Allemagne] ; Anggraeni [Allemagne] ; Matthias Jarke [Allemagne] ; Marcus Specht [Pays-Bas] ; Katherine Maillet [France]Source :
- International Journal of Web Information Systems [ 1744-0084 ] ; 2010-04-06.
English descriptors
- Teeft :
- Abundant access, Active role, Aggregation, Aggregation module, Aggregator, Ajax script, Algorithm, Argyris, Authority score, Better chance, Cocorank, Cocorank algorithm, Collective decision, Collective intelligence, Content mass, Conversation mass, Database, Decentralization, Demand curve, Different forms, Different modules, Different services, Educational institutions, Entity, Explicit knowledge nodes, Food resources, Good group decision, Google, Huge variety, Ijwis, Implementation details, Inbound links, Information overload, International journal, Knowledge aggregation, Knowledge overload, Learner, Link structure, Local information, Long tail, Long tail aggregator, Long tail aggregators, Lter, Ltering, Ltering action, Ltering mechanism, Ltering mechanisms, Ltering methods, Ltering module, Mainstream products, Massive choice, Module, Next section, Niche, Niche items, Niche products, Openid, Other hand, Other learners, Overload, Pagerank, Pagerank values, Plem, Plem aggregation, Popular items, Potential solution, Private information, Query, Query time, Rank value, Rank values, Recent years, Relevant pages, Resource collection, Search engine, Search query, Second force, Similar interests, Simple interaction, Single place, Social bookmarking, Surowiecki, Surowiecki notes, Third force, User search query, Various services.
Abstract
Purpose The personal learning environment driven approach to learning suggests a shift in emphasis from a teacherdriven knowledgepush to a learnerdriven knowledgepull learning model. One concern with knowledgepull approaches is knowledge overload. The concepts of collective intelligence and the Long Tail provide a potential solution to help learners cope with the problem of knowledge overload. The paper aims to address these issues. Designmethodologyapproach Based on these concepts, the paper proposes a filtering mechanism that taps the collective intelligence to help learners find quality in the Long Tail, thus overcoming the problem of knowledge overload. Findings The paper presents theoretical, design, and implementation details of PLEM, a Web 2.0 driven service for personal learning management, which acts as a Long Tail aggregator and filter for learning. Originalityvalue The primary aim of PLEM is to harness the collective intelligence and leverage social filtering methods to rank and recommend learning entities.
Url:
DOI: 10.1108/17440081011034466
Affiliations:
- Allemagne, France, Pays-Bas
- District de Cologne, Rhénanie-du-Nord-Westphalie, Île-de-France
- Aix-la-Chapelle, Évry (Essonne)
Links toward previous steps (curation, corpus...)
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- to stream Main, to step Merge: 001901
- to stream Main, to step Curation: 001899
- to stream Main, to step Exploration: 001899
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ISTEX:9ADEE555C233FB19C642DA57DA5224BC3B940418Le document en format XML
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