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Lozano, José H.; Revuelta, Javier – Applied Measurement in Education, 2021
The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…
Descriptors: Bayesian Statistics, Computation, Learning, Testing
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Rozell, Timothy G.; Johnson, Jessica; Sexten, Andrea; Rhodes, Ashley E. – Journal of College Science Teaching, 2017
Students in a junior- and senior-level Anatomy and Physiology course have the opportunity to correct missed exam questions ("regrade") and earn up to half of the original points missed. The three objectives of this study were to determine if: (a) performance on the regrade assignment was correlated with scores on subsequent exams, (b)…
Descriptors: Physiology, Scores, Grades (Scholastic), Exit Examinations
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Huff, Mark J.; Balota, David A.; Hutchison, Keith A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
We examined whether 2 types of interpolated tasks (i.e., retrieval-practice via free recall or guessing a missing critical item) improved final recognition for related and unrelated word lists relative to restudying or completing a filler task. Both retrieval-practice and guessing tasks improved correct recognition relative to restudy and filler…
Descriptors: Testing, Guessing (Tests), Memory, Retention (Psychology)
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Wang, Lijuan; Zhang, Zhiyong – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This study investigated influences of censored data on mediation analysis. Mediation effect estimates can be biased and inefficient with censoring on any one of the input, mediation, and output variables. A Bayesian Tobit approach was introduced to estimate and test mediation effects with censored data. Simulation results showed that the Bayesian…
Descriptors: Statistical Analysis, Mediation Theory, Censorship, Bayesian Statistics