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…

Reinforcement-based interventions, the most frequently used treatments for school-age children, rely on accurately identifying stimuli that will serve to reinforce appropriate classroom behavior. Research has consistently demonstrated that the results from a forced-choice pairing procedure are the best predictors of reinforcing stimuli.…

This exploratory data mining project used distance-based clustering algorithms to study three indicators of student behavioral data collectively called AB-Index, and established a typology of six types of learners for a suburban community college. The study is based on the notion that student behavioral data are a good basis for new ways of doing…