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Bürkner, Paul-Christian – Journal of Intelligence, 2020
Raven's Standard Progressive Matrices (SPM) test and related matrix-based tests are widely applied measures of cognitive ability. Using Bayesian Item Response Theory (IRT) models, I reanalyzed data of an SPM short form proposed by Myszkowski and Storme (2018) and, at the same time, illustrate the application of these models. Results indicate that…
Descriptors: Intelligence Tests, Matrices, Bayesian Statistics, Item Response Theory
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Lozano, José H.; Revuelta, Javier – Educational and Psychological Measurement, 2023
The present paper introduces a general multidimensional model to measure individual differences in learning within a single administration of a test. Learning is assumed to result from practicing the operations involved in solving the items. The model accounts for the possibility that the ability to learn may manifest differently for correct and…
Descriptors: Bayesian Statistics, Learning Processes, Test Items, Item Analysis
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Bartsch, Lea M.; Shepherdson, Peter – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Previous research indicates that long-term memory (LTM) may contribute to performance in working memory (WM) tasks. Across 3 experiments, we investigated the extent to which active maintenance in WM can be replaced by relying on information stored in episodic LTM, thereby freeing capacity for additional information in WM. First, participants…
Descriptors: Short Term Memory, Task Analysis, Recall (Psychology), German
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Rodríguez-Vásquez, Flor Monserrat; Ariza-Hernandez, Francisco J. – EURASIA Journal of Mathematics, Science and Technology Education, 2021
The evaluation of learning in mathematics is a worldwide problem, therefore, new methods are required to assess the understanding of mathematical concepts. In this paper, we propose to use the Item Response Theory to analyze the understanding level of undergraduate students about the real function mathematical concept. The Bayesian approach was…
Descriptors: Bayesian Statistics, Mathematics Education, Item Response Theory, Undergraduate Students
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Lloyd, Kevin; Sanborn, Adam; Leslie, David; Lewandowsky, Stephan – Cognitive Science, 2019
Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…
Descriptors: Short Term Memory, Bayesian Statistics, Cognitive Ability, Individual Differences
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Dorambari, Diedon – International Journal of Education and Practice, 2022
This study examined whether instructional humor (IH) was not just another type of seductive detail when covariates such as humor pre-disposition, prior-knowledge, and working memory capacity were controlled. Participants were students (N = 228) from universities who were randomly assigned two stimuli conditions in the classic experimental design.…
Descriptors: Humor, Multimedia Instruction, Prior Learning, Short Term Memory
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Ricker, Timothy J.; Vergauwe, Evie; Hinrichs, Garrett A.; Blume, Christopher L.; Cowan, Nelson – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
There is substantial debate in the field of short-term memory (STM) as to whether the process of active maintenance occurs through memory-trace reactivation or repair. A key difference between these 2 potential mechanisms is that a repair mechanism should lead to recovery of forgotten information. The ability to recover forgotten memories would be…
Descriptors: Cognitive Ability, Maintenance, Short Term Memory, Retention (Psychology)
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Khajah, Mohammad; Lindsey, Robert V.; Mozer, Michael C. – International Educational Data Mining Society, 2016
In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better.…
Descriptors: Bayesian Statistics, Data Analysis, Prediction, Intelligent Tutoring Systems
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Hamlin, J. Kiley; Ullman, Tomer; Tenenbaum, Josh; Goodman, Noah; Baker, Chris – Developmental Science, 2013
Evaluating individuals based on their pro- and anti-social behaviors is fundamental to successful human interaction. Recent research suggests that even preverbal infants engage in social evaluation; however, it remains an open question whether infants' judgments are driven uniquely by an analysis of the mental states that motivate others' helpful…
Descriptors: Infants, Social Cognition, Bayesian Statistics, Infant Behavior
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van Viersen, Sietske; Kroesbergen, Evelyn H.; Slot, Esther M.; de Bree, Elise H. – Journal of Learning Disabilities, 2016
This study investigated how gifted children with dyslexia might be able to mask literacy problems and the role of possible compensatory mechanisms. The sample consisted of 121 Dutch primary school children that were divided over four groups (typically developing [TD] children, children with dyslexia, gifted children, gifted children with…
Descriptors: Dyslexia, Academically Gifted, Reading Skills, Elementary School Students
Hill, Jennifer Lynn; Su, Yu-Sung – Grantee Submission, 2013
Causal inference in observational studies typically requires making comparisons between groups that are dissimilar. For instance, researchers investigating the role of a prolonged duration of breastfeeding on child outcomes may be forced to make comparisons between women with substantially different characteristics on average. In the extreme there…
Descriptors: Nutrition, Comparative Analysis, Child Development, Cognitive Ability
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Gray, Geraldine; McGuinness, Colm; Owende, Philip; Carthy, Aiden – Journal of Learning Analytics, 2014
Increasing college participation rates, and diversity in student population, is posing a challenge to colleges in their attempts to facilitate learners achieve their full academic potential. Learning analytics is an evolving discipline with capability for educational data analysis that could enable better understanding of learning process, and…
Descriptors: Psychometrics, Data Analysis, Academic Achievement, Postsecondary Education
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Xu, Jing; Griffiths, Thomas L. – Cognitive Psychology, 2010
Many human interactions involve pieces of information being passed from one person to another, raising the question of how this process of information transmission is affected by the cognitive capacities of the agents involved. Bartlett (1932) explored the influence of memory biases on the "serial reproduction" of information, in which one…
Descriptors: Stimuli, Memory, Bayesian Statistics, Prediction
Jannarone, Robert J. – 1986
A variety of locally dependent models are introduced having individual difference parameters that may be interpreted as reflecting effective learning abilities. One version is a univariate extension of the Rasch model with a Markov property: the probability that a given individual will pass an item depends on previous items only through the…
Descriptors: Academic Aptitude, Bayesian Statistics, Cognitive Ability, Estimation (Mathematics)