Comparative Judgement (CJ) aims to improve the quality of performance-based assessments by letting multiple assessors judge pairs of performances. CJ is generally associated with high levels of reliability, but there is also a large variation in reliability between assessments. This study investigates which assessment characteristics influence the…

Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…

In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…

This study examined the relative effectiveness of Bayesian model comparison methods in selecting an appropriate graded response (GR) model for performance assessment applications. Three popular methods were considered: deviance information criterion (DIC), conditional predictive ordinate (CPO), and posterior predictive model checking (PPMC). Using…

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 can be instrumental in this process, as they can present a broad range of complex scenarios without involving harm to people or property. However, "automatic"…