Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…

Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…

It has been recognized that in order to drive Intelligent Tutoring Systems (ITSs) into mainstream use by the teaching community, it is essential to support teachers through the entire ITS process: Design, Development, Deployment, Reflection and Adaptation. Although research has been done on supporting teachers through design to deployment of ITSs,…

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…