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Michael Röbner; Karin Binder; Corbinian Geier; Stefan Krauss – Educational Studies in Mathematics, 2025
It has been established that, in Bayesian tasks, performance and typical errors in reading information from filled visualizations depend both on the type of the provided visualization and information format. However, apart from reading visualizations, students should also be able to create visualizations on their own and successfully use them as…
Descriptors: Academic Achievement, Error Patterns, Probability, Visualization
Cutter, Michael G.; Martin, Andrea E.; Sturt, Patrick – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
We investigated whether readers use the low-level cue of proper noun capitalization in the parafovea to infer syntactic category, and whether this results in an early update of the representation of a sentence's syntactic structure. Participants read sentences containing either a subject relative or object relative clause, in which the relative…
Descriptors: Nouns, Phrase Structure, Syntax, Eye Movements
Evans, William S.; Cavanaugh, Robert; Quique, Yina; Boss, Emily; Starns, Jeffrey J.; Hula, William D. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: The purpose of this study was to develop and pilot a novel treatment framework called "BEARS" (Balancing Effort, Accuracy, and Response Speed). People with aphasia (PWA) have been shown to maladaptively balance speed and accuracy during language tasks. BEARS is designed to train PWA to balance speed-accuracy trade-offs and…
Descriptors: Accuracy, Semantics, Aphasia, Reaction Time
Holden, Mark P.; Newcombe, Nora S.; Shipley, Thomas F. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan,…
Descriptors: Spatial Ability, Memory, Models, Task Analysis
Peer reviewedTatsuoka, Kikumi K.; Tatsuoka, Maurice M. – Psychometrika, 1987
The rule space model permits measurement of cognitive skill acquisition and error diagnosis. Further discussion introduces Bayesian hypothesis testing and bug distribution. An illustration involves an artificial intelligence approach to testing fractions and arithmetic. (Author/GDC)
Descriptors: Bayesian Statistics, Cognitive Measurement, Error Patterns, Hypothesis Testing

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