Publication: Granules for learning behavior
Issued Date
2013-12-01
Resource Type
ISSN
09226389
Other identifier(s)
2-s2.0-84894583104
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Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Frontiers in Artificial Intelligence and Applications. Vol.253, (2013), 191-204
Suggested Citation
Sumalee Sonamthiang, Kanlaya Naruedomkul, Nick Cercone Granules for learning behavior. Frontiers in Artificial Intelligence and Applications. Vol.253, (2013), 191-204. doi:10.3233/978-1-61499-258-5-191 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/31603
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Title
Granules for learning behavior
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Abstract
This chapter presents an innovative approach to discover granular learning behavior patterns of students learning interactions with an intelligent tutoring system (ITS). The approach is domain independent and able to manage learning behavior uncertainty. An N-gram analysis is used to model the learning behavior from the learning action streams to obtain regular and irregular learning behavior patterns. Then, the N-gram models are clustered into a hierarchy using a rough set-based map granule. The hierarchical pattern can be used to improve the domain knowledge of an ITS in predicting student's actions, sequencing problems to be solved, and adjusting hint mechanisms. © 2013 The authors and IOS Press. All rights reserved.