Diagnostic, predictive and compositional modeling with data mining in integrated learning environments

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 comp...

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Main Author: LEE, C
Format: Article
Language:English
Published: PERGAMON-ELSEVIER SCIENCE LTD 2007
Subjects:
Online Access:http://shdl.mmu.edu.my/2985/
http://shdl.mmu.edu.my/2985/1/1015.pdf
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author LEE, C
author_facet LEE, C
author_sort LEE, C
building MMU Institutional Repository
collection Online Access
description 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.
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spelling mmu-29852014-02-13T09:07:30Z http://shdl.mmu.edu.my/2985/ Diagnostic, predictive and compositional modeling with data mining in integrated learning environments LEE, C T Technology (General) QA75.5-76.95 Electronic computers. Computer science 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. PERGAMON-ELSEVIER SCIENCE LTD 2007-11 Article NonPeerReviewed text en http://shdl.mmu.edu.my/2985/1/1015.pdf LEE, C (2007) Diagnostic, predictive and compositional modeling with data mining in integrated learning environments. Computers & Education, 49 (3). 562-580 . ISSN 03601315 http://dx.doi.org/10.1016/j.compedu.2005.10.010 doi:10.1016/j.compedu.2005.10.010 doi:10.1016/j.compedu.2005.10.010
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
LEE, C
Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title_full Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title_fullStr Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title_full_unstemmed Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title_short Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
title_sort diagnostic, predictive and compositional modeling with data mining in integrated learning environments
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2985/
http://shdl.mmu.edu.my/2985/
http://shdl.mmu.edu.my/2985/
http://shdl.mmu.edu.my/2985/1/1015.pdf