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 …

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

There are many ways to address the design of automated scoring systems for complex
constructed response tasks. This volume illustrates a variety of such methods, as well as …

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 …

Digital games offer an appealing environment for assessing student proficiencies, including
skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian …

Digital game-based assessments generate student process data that is much more difficult
to analyze than traditional assessments. The formative nature of game-based assessments …

A central challenge in using learning progressions (LPs) in practice is modeling the
relationships that link student performance on assessment tasks to students' levels on the …

Educational assessments that exploit advances in technology and cognitive psychology can
produce observations and pose student models that outstrip familiar test-theoretic models …

Bayesian inference networks, a synthesis of statistics and expert systems, have advanced
reasoning under uncertainty in medicine, business, and social sciences. This innovative …