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

被引:11
|
作者
Lee, Chien-Sing [1 ]
机构
[1] Multimedia Univ, Fac Informat Technol, Cyberjaya 63100, Selangor, Malaysia
关键词
intelligent tutoring systems; interactive learning environments; multimedia/hypermedia systems; diagnostic; predictive and compositional modeling; architectural and design patterns;
D O I
10.1016/j.compedu.2005.10.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:562 / 580
页数:19
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