Educational assessments that exploit advances in technology and cognitive psychology can produce observations and pose student models that outstrip familiar test-theoretic models and analytic methods. Bayesian inference networks (BINs), which include familiar models and techniques as special cases, can be used to manage belief about students'…

Multiple matrix sampling (MMS) theory indicates how data may be gathered to most efficiently convey information about levels of attainment in a population, but standard analyses of these data require random sampling of items from a fixed pool of items. This assumption proscribes the retirement of flawed or obsolete items from the pool as well as…

California Assessment Program's application of matrix sampling and item response curve theory to the scaling and reporting of state assessment data is described. It is designed to express educational outcomes in an efficient and interpretable form that is both immediately informative and suited to analysis over extended periods of time.…