Title
Plem: A Web 2.0 Driven Long Tail Aggregator And Filter For E-Learning
Abstract
Purpose - The personal learning environment driven approach to learning suggests a shift in emphasis from a teacher-driven knowledge-push to a learner-driven knowledge-pull learning model. One concern with knowledge-pull 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.Design/methodology/approach - 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.Originality/value - The primary aim of PLEM is to harness the collective intelligence and leverage social filtering methods to rank and recommend learning entities.
Year
DOI
Venue
2010
10.1108/17440081011034466
INTERNATIONAL JOURNAL OF WEB INFORMATION SYSTEMS
Keywords
Field
DocType
E-learning, Knowledge capture, Self managed learning
Data mining,World Wide Web,E learning,News aggregator,Computer science,Personal learning environment,Wisdom of crowds,Web 2.0,Knowledge capture,Web information,Personalization
Journal
Volume
Issue
ISSN
6
1
1744-0084
Citations 
PageRank 
References 
3
0.38
2
Authors
5
Name
Order
Citations
PageRank
Mohamed Amine Chatti145843.01
Anggraeni230.38
Matthias Jarke350711762.03
Marcus Specht41109142.35
Katherine Maillet581.16