This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

Traditional estimators of item response theory scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of the standard errors of measurement (SEMs). Here, the authors review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical…

There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…

Educational assessment concerns inference about student knowledge, skills, and accomplishments. Test theory has evolved in part to address questions of weight, coverage, and import of data. Resulting concepts and techniques can be viewed as applications of more general principles for inference in the presence of uncertainty. (SLD)

The Computer-Assisted Data Analysis (CADA) Monitor is a set of conversational-language interactive computer programs that permit relatively inexperienced persons to perform relatively complex statistical data analysis. The Monitor leads the user through an analysis on a step-by-step basis providing the necessary direction, information, and…

Model checking is a crucial part of any statistical analysis. As educators tie models for testing to cognitive theory of the domains, there is a natural tendency to represent participant proficiencies with latent variables representing the presence or absence of the knowledge, skills, and proficiencies to be tested (Mislevy, Almond, Yan, &…

Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…

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…