Modeling the Macro-Behavior of Learning Object Repositories

Abstract

Learning Object Repositories (LOR) are the result of the activity of hundreds or thousands of contributing individuals. It has been shown in Ochoa & Duval, 2009 that LOR have an interesting macro-behavior, mostly governed by long-tailed distributions. The shape of these distributions provides valuable information for the management and operation of LORs. However, the reason why these distributions appear is not known. This work proposes a simple model to explain this macro-behavior the consequence of the very simple micro-behavior of individual contributors, more specifically their number, production rate and lifetime in the repository. This model is formally presented and successfully validated against data from existing LORs. While simple, this model seems to explain most of the large-scale measurements in function of the small-scale interactions. Finally, this work discusses the implications that this model has in the planning and maintenance of new and existing LORs.