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Williamson, David M.; Mislevy, Robert J.; Almond, Russell G. – 2001
This study investigated statistical methods for identifying errors in Bayesian networks (BN) with latent variables, as found in intelligent cognitive assessments. BN, commonly used in artificial intelligence systems, are promising mechanisms for scoring constructed-response examinations. The success of an intelligent assessment or tutoring system…
Descriptors: Artificial Intelligence, Bayesian Statistics, Cognitive Tests, Mathematical Models
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Beland, Anne; Mislevy, Robert J. – Journal of Educational Measurement, 1996
This article addresses issues in model building and statistical inference in the context of student modeling. The use of probability-based reasoning to explicate hypothesized and empirical relationships and to structure inference in the context of proportional reasoning tasks is discussed. Ideas are illustrated with an example concerning…
Descriptors: Cognitive Psychology, Models, Networks, Probability
Mislevy, Robert J.; Gitomer, Drew H. – 1995
Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring…
Descriptors: Bayesian Statistics, Clinical Diagnosis, Educational Theories, Hydraulics
Mislevy, Robert J. – 1994
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,…
Descriptors: Bayesian Statistics, Cognitive Processes, Cognitive Psychology, Educational Diagnosis
Mislevy, Robert J.; Almond, Russell G.; Yan, Duanli; Steinberg, Linda S. – 2000
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'…
Descriptors: Bayesian Statistics, Educational Assessment, Educational Technology, Educational Testing
Mislevy, Robert J. – 1991
This paper lays out a framework for comparing the qualities and the quantities of information about student competence provided by multiple-choice and free-response test items. After discussing the origins of multiple-choice testing and recent influences for change, the paper outlines an "inference network" approach to test theory, in…
Descriptors: Cognitive Psychology, Competence, Elementary Secondary Education, Inferences