Data mining techniques for building student groups

Danuta Zakrzewska

Abstract


Finding student groups of similar preferences enables to adjust e-learning systems according to their needs. In the paper, it is compared usage of different data mining techniques for creating learners’ groups. It is considered application of supervised and unsupervised classification as well as frequent pattern mining.

Keywords


adaptive e-learning systems; grouping; classification; frequent pattern mining

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References


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DOI: http://dx.doi.org/10.21936/si2010_v31.n2B.416