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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
van der Linden, Wim J. – Applied Psychological Measurement, 2009
An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…
Descriptors: Simulation, Adaptive Testing, Vocational Aptitude, Bayesian Statistics
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
Haladyna, Tom; Roid, Gale – 1980
An empirical review of test items is described as an essential step in criterion-referenced test development. The concept of test items' instructional sensitivity is introduced, and research is briefly reviewed which describes four theoretical contexts in which instructional sensitivity indexes have been observed: criterion-referenced; classical…
Descriptors: Achievement Tests, Bayesian Statistics, Course Objectives, Criterion Referenced Tests