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Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
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DOI：10.1016/j.compedu.2005.10.010.png)
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Abstract
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Models represent a set of generic patterns to test hypotheses. This paper presents the CogMoLab student model in the context of an integrated learning environment. Three aspects are discussed: diagnostic and predictive modeling with respect to the issues of credit assignment and scalability and compositional modeling of the student profile in the context of an intelligent tutoring system/adaptive hypermedia learning system architectural pattern. The SOM-PCA, a collaborative-based data mining approach, is shown to be reusable for all three purposes above, enabling fast, objective implementations without requiring much intensive data collection. (C) 2005 Elsevier Ltd. All rights reserved.
Keywords:
intelligent tutoring systems
interactive learning environments
multimedia/hypermedia systems
diagnostic, predictive and compositional modeling
architectural and design patterns
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