In this paper we describe the development and refinement of "evidence rules" and "measurement models" within the "evidence model" of the "evidence-centered design" (ECD) framework in the context of the "Packet Tracer" digital learning environment of the "Cisco Networking Academy." Using…

We are currently at an exciting juncture in developing effective means for assessing so-called 21st-century skills in an innovative yet reliable fashion. One of these avenues leads through the world of "epistemic games" (Shaffer, 2006a), which are games designed to give learners the rich experience of professional practica within a discipline.…

A major issue in the study of learning progressions (LPs) is linking student performance on assessment tasks to the progressions. This report describes the challenges faced in making this linkage using Bayesian networks to model LPs in the field of computer networking. The ideas are illustrated with exemplar Bayesian networks built on Cisco…

From a contemporary perspective on cognition, the between-persons variables in trait-based arguments in educational assessment are absurd over-simplifications. Yet, for a wide range of applications, they work. Rather than seeing such variables as independently-existing characteristics of people, we can view them as summaries of patterns in…

Recent developments in cognitive and educational psychology, such as increased appreciation of the situated nature of learning and understanding, call for broader ranges of student models and types of data than those standard in testing today. We must specify how what we observe on the test is related to competence as we conceptualize it, and…

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)

Recent developments in cognitive psychology suggest models for knowledge and learning that often fall outside the realm of standard test theory. This paper concerns probability-based inference in terms of such models. The essential idea is to define a space of "student models"--simplified characterizations of students' knowledge, skill,…