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Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego – Journal of Educational Measurement, 2007
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Descriptors: Inferences, Models, Item Response Theory, Cognitive Measurement

Wang, Tianyou; Vispoel, Walter P. – Journal of Educational Measurement, 1998
Used simulations of computerized adaptive tests to evaluate results yielded by four commonly used ability estimation methods: maximum likelihood estimation (MLE) and three Bayesian approaches. Results show clear distinctions between MLE and Bayesian methods. (SLD)
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing

De Ayala, R. J.; And Others – Journal of Educational Measurement, 1990
F. M. Lord's flexilevel, computerized adaptive testing (CAT) procedure was compared to an item-response theory-based CAT procedure that uses Bayesian ability estimation with various standard errors of estimates used for terminating the test. Ability estimates of flexilevel CATs were as accurate as were those of Bayesian CATs. (TJH)
Descriptors: Ability Identification, Adaptive Testing, Bayesian Statistics, Comparative Analysis