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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
Stephen Ferrigno; Samuel J. Cheyette; Susan Carey – Cognitive Science, 2025
Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…
Descriptors: Sequential Learning, Cognitive Processes, Knowledge Representation, Training
Lucia Sweeney; Elena Plante; Heidi M. Mettler; Jessica Hall; Rebecca Vance – Language, Speech, and Hearing Services in Schools, 2024
Purpose: Although conversational recast treatment is generally efficacious, there are many ways in which the individual components of the treatment can be delivered. Some of these are known to enhance treatment, others appear to interfere with learning, and still others appear to have no impact at all. This study tests the potential effect of…
Descriptors: Preschool Children, Grammar, Error Patterns, Outcome Measures
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Ross, Linette P. – ProQuest LLC, 2022
One of the most serious forms of cheating occurs when examinees have item preknowledge and prior access to secure test material before taking an exam for the purpose of obtaining an inflated test score. Examinees that cheat and have prior knowledge of test content before testing may have an unfair advantage over examinees that do not cheat. Item…
Descriptors: Testing, Deception, Cheating, Identification
Abu-Ghazalah, Rashid M.; Dubins, David N.; Poon, Gregory M. K. – Applied Measurement in Education, 2023
Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…
Descriptors: Guessing (Tests), Multiple Choice Tests, Probability, Models
Paape, Dario; Avetisyan, Serine; Lago, Sol; Vasishth, Shravan – Cognitive Science, 2021
We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better…
Descriptors: Computational Linguistics, Indo European Languages, Grammar, Bayesian Statistics
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
Nguyen, Huy; Liew, Chun Wai – International Educational Data Mining Society, 2018
Recent works on Intelligent Tutoring Systems have focused on more complicated knowledge domains, which pose challenges in automated assessment of student performance. In particular, while the system can log every user action and keep track of the student's solution state, it is unable to determine the hidden intermediate steps leading to such…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Data Analysis, Error Patterns
Rafferty, Anna N.; Jansen, Rachel A.; Griffiths, Thomas L. – Cognitive Science, 2020
Online educational technologies offer opportunities for providing individualized feedback and detailed profiles of students' skills. Yet many technologies for mathematics education assess students based only on the correctness of either their final answers or responses to individual steps. In contrast, examining the choices students make for how…
Descriptors: Computer Assisted Testing, Mathematics Tests, Mathematics Skills, Student Evaluation
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
Johnston, Angie M.; Johnson, Samuel G. B.; Koven, Marissa L.; Keil, Frank C. – Developmental Science, 2017
Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists--such as Einstein--do? Four experiments support the latter possibility. In particular, we…
Descriptors: Young Children, Thinking Skills, Inferences, Bayesian Statistics
Suh, Youngsuk; Cho, Sun-Joo; Bottge, Brian A. – Grantee Submission, 2018
This article presents a multilevel longitudinal nested logit model for analyzing correct response and error types in multilevel longitudinal intervention data collected under a pretest-posttest, cluster randomized trial design. The use of the model is illustrated with a real data analysis, including a model comparison study regarding model…
Descriptors: Hierarchical Linear Modeling, Longitudinal Studies, Error Patterns, Change
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
Braem, Senne; Liefooghe, Baptist; De Houwer, Jan; Brass, Marcel; Abrahamse, Elger L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
Unlike other animals, humans have the unique ability to share and use verbal instructions to prepare for upcoming tasks. Recent research showed that instructions are sufficient for the automatic, reflex-like activation of responses. However, systematic studies into the limits of these automatic effects of task instructions remain relatively…
Descriptors: Responses, Context Effect, Visual Stimuli, Performance

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