Clustering by usage: higher order co-occurrences of learning objects

Authors:
Katja Niemann;Hans-Christian Schmitz;Uwe Kirschenmann;Martin Wolpers;Anna Schmidt;Tim Krones
Affiliations:
Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany;Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany;Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany;Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany;Saarland University, Saarbrücken, Germany;Saarland University, Saarbrücken, Germany
Venue:
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Year:
2012

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Abstract

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analyzing their usage in a web portal. Our approach does not rely on the content of the learning objects or on the relations between the users and the learning objects but on usage-based relations between the objects themselves. The technique we apply for calculating higher order co-occurrences to create semantically homogenous clusters of data objects is taken from corpus driven lexicology where it is used to cluster words. We expect the members of a higher order co-occurrence class to be similar according to their content and present the evaluations of that assumption using two teaching and learning systems.