Simulations and games offer interactive tasks that can elicit rich data, providing evidence of complex skills that are difficult to measure with more conventional items and tests. However, one notable challenge in using such technologies is making sense of the data generated in order to make claims about individuals or groups. This article…

Simulations provide opportunities for individuals to learn and develop skills for situations that may be expensive, time-consuming, or dangerous. Careful design can support a person's learning by tailoring the features of situations to his or her skill level(s), allowing repeated attempts, and by providing timely feedback. Furthermore, simulations…

If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking, a flexible family of model-checking procedures, as a tool for criticizing models due to unaccounted for dimensions in the context of item response theory. Factors…

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are…

Presents a design framework that incorporates integrated structures for modeling knowledge and skills, designing tasks, and extracting and synthesizing evidence. Illustrates these ideas in the context of a project that assesses problem solving in dental hygiene through computer-based simulations. (SLD)

Marginal maximum likelihood estimation equations are derived for the structural parameters of the Saltus model, and a computing approximation is suggested based on the EM algorithm. The solution is illustrated with simulated data and an example from the domain of mixed number subtraction. (SLD)

The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…