Computer Science – Artificial Intelligence
Scientific paper
2009-01-29
Computer Science
Artificial Intelligence
Proceedings of the 7th Mexican International Conference on Artificial Intelligence (MICAI 2008), Springer, pp. 765-778
Scientific paper
10.1007/978-3-540-88636-5
Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problemsolving learning activities. However, for many ill-defined domains, the domain knowledge is hard to define explicitly. In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions, and how it can support tutoring services during problem-solving exercises. This article describes an extension of this approach to extract a problem space that is richer and more adapted for supporting tutoring services. We combined sequential pattern mining with (1) dimensional pattern mining (2) time intervals, (3) the automatic clustering of valued actions and (4) closed sequences mining. Some tutoring services have been implemented and an experiment has been conducted in a tutoring system.
Fournier-Viger Philippe
Nguifo Engelbert Mephu
Nkambou Roger
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