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Download full textSilva, R. M.; Guan, Y.; Swartz, T. B. – Journal on Efficiency and Responsibility in Education and Science, 2017
This paper attempts to bridge the gap between classical test theory and item response theory. It is demonstrated that the familiar and popular statistics used in classical test theory can be translated into a Bayesian framework where all of the advantages of the Bayesian paradigm can be realized. In particular, prior opinion can be introduced and…
Descriptors: Item Response Theory, Bayesian Statistics, Test Construction, Markov Processes
Matthews-Lopez, Joy L.; Hombo, Catherine M. – 2001
The purpose of this study was to examine the recovery of item parameters in simulated Automatic Item Generation (AIG) conditions, using Markov chain Monte Carlo (MCMC) estimation methods to attempt to recover the generating distributions. To do this, variability in item and ability parameters was manipulated. Realistic AIG conditions were…
Descriptors: Estimation (Mathematics), Monte Carlo Methods, Statistical Distributions, Test Construction
Peer reviewedSchiel, Jeffrey L.; Shaw, Dale G. – Applied Measurement in Education, 1992
Changes in information retention resulting from changes in reliability and number of intervals in scale construction were studied to provide quantitative information to help in decisions about choosing intervals. Information retention reached a maximum when the number of intervals was about 8 or more and reliability was near 1.0. (SLD)
Descriptors: Decision Making, Knowledge Level, Mathematical Models, Monte Carlo Methods
