An Automatic Classification and Clustering Algorithm for Online Learning Goals Based on Cognitive Thinking

Ying Wang, Weifeng Jiang


To improve the learning effect of online learning, an online learning target automatic classification and clustering analysis algorithm based on cognitive thinking was proposed. It was applied to a multi-dimensional learning community. A new form of virtual learning community concept was proposed. The design ideas of its multi-dimensional learning environment were elaborated. Ontology technology was used to collect student learning process data. A cognitive diagnostic model for assessing student learning status was generated. Finally, through the cluster analysis technology, the registered students in the curriculum center were automatically divided into different levels of community groups. The results showed that the proposed algorithm for automatic classification and clustering of online learning targets had a good application effect in the learning community. Therefore, this method has practical application value.


online learning; cluster analysis; virtual learning community; cognitive diagnosis model

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Copyright (c) 2018 Ying Wang, Weifeng Jiang

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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