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Quantitative analysis of learning object repositories

Authors :
Erik Duval
Xavier Ochoa
Source :
IEEE Transactions on Learning Technologies
Publication Year :
2009
Publisher :
IEEE, 2009.

Abstract

Learning Object Repositories (LOR) are the backbone of the Learning Object Economy. However, little is known about how big they are, how they grow over time, what are the distribution of the contribution among their users or the popularity of their contents. This paper is a first step to measure these operational aspects of Learning Object Repositories and Referatories through a series of quantitative analysis. Measuring key aspects of the production and consumption of Learning Objects is a new sub-field of Informetrics that we call “Learnometrics”. The analyses are performed on current data from widely used LOR’s. The results confirm some long held beliefs, but also point out some new issues: LORs grow linearly, contribution distribution follows a power law and popularity of objects follows a log-normal distribution. The paper discusses the implications of these findings for the LOR community. Outstanding paper award. ispartof: pages:6031-6048 ispartof: Proceedings of EdMedia08: World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 pages:6031-6048 ispartof: EdMedia08: World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 location:Vienna, Austria status: published

Details

Language :
English
Database :
OpenAIRE
Journal :
IEEE Transactions on Learning Technologies
Accession number :
edsair.doi.dedup.....679ff7469c0425aa00b7eff4bd81363c