Recommending learning objects according to a teachers' contex model
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
Metrics-based evaluation of learning object reusability
Software Quality Control
Statistical profiles of highly-rated learning objects
Computers & Education
Learnometrics: metrics for learning objects
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Evaluating collaborative filtering recommendations inside large learning object repositories
Information Processing and Management: an International Journal
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This paper conducts the first detailed quantitative study of the process of publication of learning objects in repositories. This process has been often discussed theoretically, but never empirically evaluated. Several question related to basic characteristics of the publication process are raised at the beginning of the paper and answered through quantitative analysis. To provide a wide view of the publication process, this paper analyzes four types of repositories: Learning Object Repositories, Learning Object Referatories, Open Courseware Initiatives, and Learning Management Systems. For comparison, Institutional Repositories are also analyzed. Three repository characteristics are measured: size, growth, and contributor base. The main findings are that the amount of learning objects is distributed among repositories according to a power law, the repositories mostly grow linearly, and the amount of learning objects published by each contributor follows heavy-tailed distributions. The paper finally discusses the implications that this findings could have in the design and operation of Learning Object Repositories.