Towards educational data mining: Using data mining methods for automated chat analysis to understand and support inquiry learning processes

Anjo Anjewierden (1) , Bas Kolloffel (1) , Casper Hulshof (1)

1 Department of Instructional Technology

In this paper we investigate the application of data mining methods to provide learners with real-time adaptive feedback on the nature and patterns of their on-line communication while learning collaboratively.We derived two models for classifying chat messages using data mining techniques and tested these on an actual data set [16]. The reliability of the classification of chat messages is established by comparing the models performance to that of humans. Results indicate that the classification of messages is reasonably reliable and can thus be done automatically and in real-time. This makes it, for example, possible to increase the awareness of learners by visualizing their interaction behaviour by means of avatars. It is concluded that the application of data mining methods to educational chats is both feasible and can, over time, result in the improvement of learning environments.

Keywords: automated chat analysis; adaptive feedback

Domains: Computer Science [cs]; Technology for Human Learning

Anjo Anjewierden, Bas Kolloffel, Casper Hulshof. Towards educational data mining: Using data mining methods for automated chat analysis to understand and support inquiry learning processes. International Workshop on Applying Data Mining in e-Learning (ADML 2007), 2007, Crete, Greece. ⟨hal-00190067⟩