As the popularity of rich assessment scenarios increases so must the availability of
psychometric models capable of handling the resulting data. Dynamic Bayesian networks …

Bayesian networks (BN) provide a convenient and intuitive framework for specifying
complex joint probability distributions and are thus well suited for modeling content domains …

Designing, developing, and administering assessments has remained fairly unchanged
across the past century. However, recent developments in instructional technology, learning …

This paper defines Bayesian network models and examines their applications to IRT‐based
cognitive diagnostic modeling. These models are especially suited to building inference …

With Partially Observable Markov Decision Processes (POMDPs), Intelligent Tutoring
Systems (ITSs) can model individual learners from limited evidence and plan ahead despite …

Although much research has been conducted on the psychometric properties of cognitive
diagnostic models, they are only recently being used in operational settings to provide …

We investigate the relationship between Bayesian inference networks (BayesNets) and
diagnostic classification models (DCMs). Specifically, we demonstrate and empirically …

Assessment of complex task performance is crucial to evaluating personnel in critical job
functions such as Navy damage control operations aboard ships. Games and simulations …

Abstract According to Pearson's Law:“That which is measured improves.” But some
important constructs, like problem-solving skill, are generally viewed as very difficult to …

To achieve adaptive learning, a dynamic assessment system equipped with a cognitive
diagnosis was developed for this study, which adopts a three-stage model of diagnosis …