Quantitative Analysis of Learning Object Repositories
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.