Diagnostic, predictive and compositional modeling with data mining in integrated learning environments
Computers & Education Volume 49, Number 3, ISSN 0360-1315 Publisher: Elsevier Ltd
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.
Lee, C.S. (2007). Diagnostic, predictive and compositional modeling with data mining in integrated learning environments. Computers & Education, 49(3), 562-580. Elsevier Ltd.
- Architectural and design patterns
- Data Collection
- Diagnostic, predictive and compositional modeling
- distance education
- educational technology
- Integrated Learning Systems
- intelligent tutoring systems
- Interactive Learning Environments
- multimedia/hypermedia systems
- Student Records