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van Ravenzwaaij, Don; van der Maas, Han L. J.; Wagenmakers, Eric-Jan – Psychological Review, 2012
In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…
Descriptors: Intelligent Tutoring Systems, Inhibition, Bayesian Statistics, Decision Making
Vos, Hans J. – 1994
Some applications of Bayesian decision theory to intelligent tutoring systems are considered. How the problem of adapting the appropriate amount of instruction to the changing nature of a student's capabilities during the learning process can be situated in the general framework of Bayesian decision theory is discussed in the context of the…
Descriptors: Bayesian Statistics, Decision Making, Foreign Countries, Intelligent Tutoring Systems
Hambleton, Ronald K.; Swaminathan, H. – 1985
Comments are made on the review papers presented by six Dutch psychometricians: Ivo Molenaar, Wim van der Linden, Ed Roskam, Arnold Van den Wollenberg, Gideon Mellenbergh, and Dato de Gruijter. Molenaar has embraced a pragmatic viewpoint on Bayesian methods, using both empirical and pure approaches to solve educational research problems. Molenaar…
Descriptors: Bayesian Statistics, Decision Making, Elementary Secondary Education, Foreign Countries
van der Linden, Wim J. – 1987
The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be identified as a specific configuration of one or…
Descriptors: Bayesian Statistics, Classification, Decision Making, Foreign Countries
van der Linden, Wim J. – 1985
This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…
Descriptors: Bayesian Statistics, Classification, Cutting Scores, Decision Making
Haladyna, Tom; Roid, Gale – 1980
The problems associated with misclassifying students when pass-fail decisions are based on test scores are discussed. One protection against misclassification is to set a confidence interval around the cutting score. Those whose scores fall above the interval are passed; those whose scores fall below the interval are failed; and those whose scores…
Descriptors: Bayesian Statistics, Classification, Comparative Analysis, Criterion Referenced Tests

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