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RWTH Aachen
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A Dynamic Topic Model of Learning Analytics Research

Year 2013
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Research on learning analytics and educational data mining has been published since the first conference on Educational Data Mining (EDM) in 2008 and gained momentum through the establishment of the Learning Analytics and Knowledge (LAK) conference in 2011. This paper addresses the LAK Data Challenge from the perspective of visual analytics of topic dynamics in the LAK Dataset between 2008 and 2012. The data set was processed using probabilistic, dynamic topic mining algorithms. To enable exploration and visual analysis of the resulting topic model by LAK researchers and stakeholders we developed and deployed D-VITA, a web-based browsing tool for dynamic topic models. In this paper we explore answers to the questions about past, present, and future of LAK posed in the Data Challenge based on a topic model of all papers in the LAK Dataset. We also briefly describe how users can explore the LAK topic model on their own using D-VITA.

Details

Proceedings of the LAK Data Challenge, Leuven, Belgium, April 9, 2013, CEUR Workshop Proceedings, Vol. 974, 1-5.

Authors

Presented at

LAK Data Challenge 2013, 2013 , Leuven , BE.

Published in

Proceedings of the LAK Data Challenge, held at LAK 2013, the Third Conference on Learning Analytics and Knowledge , by Mathieu d'Aquin, Stefan Dietze, Hendrik Drachsler, Eelco Herder, Davide Taibi .

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