The purpose of this study was to examine the use of a misspecified calibration model and its impact on proficiency classification. Monte Carlo simulation methods were employed to compare competing models when the true structure of the data is known (i.e., testlet conditions). The conditions used in the design (e.g., number of items, testlet to…

Covariates have been used in mixture IRT models to help explain why examinees are classed into different latent classes. Previous research has considered manifest variables as covariates in a mixture Rasch analysis for prediction of group membership. Latent covariates, however, are more likely to have higher correlations with the latent class…

This article proposes a generalized distance discriminating method for test with polytomous response (GDD-P). The new method is the polytomous extension of an item response theory (IRT)-based cognitive diagnostic method, which can identify examinees' ideal response patterns (IRPs) based on a generalized distance index. The similarities between…

When using IRT models in Educational Achievement Testing, the model is as a rule too simple to catch all the relevant dimensions in the test. It is argued that a simple model may nevertheless be useful but that it can be complemented with additional analyses. Such an analysis, called profile analysis, is proposed and applied to the reading data of…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…