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Showing 1 to 15 of 133 results Save | Export
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Nir Shalev; Sage Boettcher; Anna C. Nobre – npj Science of Learning, 2024
Older adults struggle with tasks requiring selective attention amidst distractions. Experimental observations about age-related decline have relied on visual search designs using static displays. However, natural environments often embed dynamic structures that afford proactive anticipation of task-relevant information. We investigate the capacity…
Descriptors: Adults, Older Adults, Attention, Visual Stimuli
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Harris, Anthony M.; Eayrs, Joshua O.; Lavie, Nilli – Cognitive Research: Principles and Implications, 2023
Highly-automated technologies are increasingly incorporated into existing systems, for instance in advanced car models. Although highly automated modes permit non-driving activities (e.g. internet browsing), drivers are expected to reassume control upon a 'take over' signal from the automation. To assess a person's readiness for takeover,…
Descriptors: Eye Movements, Attention, Cognitive Processes, Reaction Time
Tiantian Sun; Ryan Bowles; Sarah N. Douglas; Joshua Plavnick – Grantee Submission, 2023
Children with complex communication needs (CCN) who use augmentative and alternative communication (AAC) often need more time to process and respond when communicating with others. This study employed a survival analysis approach exploring child response-time patterns following different communication opportunities for young children with CCN who…
Descriptors: Communication Problems, Augmentative and Alternative Communication, Reaction Time, Individual Differences
Tiantian Sun; Ryan Bowles; Sarah N. Douglas; Joshua Plavnick – Exceptional Children, 2023
Children with complex communication needs (CCN) who use augmentative and alternative communication (AAC) often need more time to process and respond when communicating with others. This study employed a survival analysis approach exploring child response-time patterns following different communication opportunities for young children with CCN who…
Descriptors: Communication Problems, Augmentative and Alternative Communication, Reaction Time, Individual Differences
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Leppink, Jimmie; Pérez-Fuster, Patricia – Educational Psychology Review, 2019
Self-rated mental effort has been and continues to be the most widely used measure of cognitive load. This single-item measure is often used as a predictor variable in linear models for predicting performance or some other response variable. While an advantage of linear models is that they are fairly easy to understand, they fall short when the…
Descriptors: Cognitive Processes, Difficulty Level, Predictor Variables, Time on Task
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Wang, Zuowei; Sabatini, John; O'Reilly, Tenaha – Scientific Studies of Reading, 2020
We compare poor-performing and normal-performing decoders' processing times on real words, pseudo-homophones, and nonwords (Study 1), and evaluate how a processing time difference is associated with rates of decoding development (Study 2). Over 800 sixth and seventh graders took an online reading component battery, which included a decoding test,…
Descriptors: Decoding (Reading), Reading Skills, Novelty (Stimulus Dimension), Reading Processes
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Harish Moni Prakash; Andrew F. Heckler – Physical Review Physics Education Research, 2025
Accuracy on assessments is commonly studied in education research but response time (RT) is relatively less investigated even though decades of research in cognitive sciences indicate that time can be an important dimension for understanding student learning. To better understand RT and the potentially important relations between accuracy and RT…
Descriptors: Reaction Time, Accuracy, Physics, Science Education
Domingue, Benjamin W.; Kanopka, Klint; Stenhaug, Ben; Sulik, Michael J.; Beverly, Tanesia; Brinkhuis, Matthieu; Circi, Ruhan; Faul, Jessica; Liao, Dandan; McCandliss, Bruce; Obradovic, Jelena; Piech, Chris; Porter, Tenelle; Soland, James; Weeks, Jon; Wise, Steven L.; Yeatman, Jason – Journal of Educational and Behavioral Statistics, 2022
The speed-accuracy trade-off (SAT) suggests that time constraints reduce response accuracy. Its relevance in observational settings--where response time (RT) may not be constrained but respondent speed may still vary--is unclear. Using 29 data sets containing data from cognitive tasks, we use a flexible method for identification of the SAT (which…
Descriptors: Accuracy, Reaction Time, Task Analysis, College Entrance Examinations
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Seyma N. Yildirim-Erbasli; Guher Gorgun – Technology, Knowledge and Learning, 2025
Exploring the relationship between student ability and test-taking effort is an important area of study, offering insights into their approach to educational assessments. Previous research shows this relationship, yet there is a scarcity of research comparing the test-taking effort of students. In addition, researchers have frequently employed…
Descriptors: Ability, Test Wiseness, Predictor Variables, Student Reaction
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Jana Welling; Timo Gnambs; Claus H. Carstensen – Educational and Psychological Measurement, 2024
Disengaged responding poses a severe threat to the validity of educational large-scale assessments, because item responses from unmotivated test-takers do not reflect their actual ability. Existing identification approaches rely primarily on item response times, which bears the risk of misclassifying fast engaged or slow disengaged responses.…
Descriptors: Foreign Countries, College Students, Guessing (Tests), Multiple Choice Tests
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Hoch, Emely; Sidi, Yael; Ackerman, Rakefet; Hoogerheide, Vincent; Scheiter, Katharina – Educational Psychology Review, 2023
It is well established in educational research that metacognitive monitoring of performance assessed by self-reports, for instance, asking students to report their confidence in provided answers, is based on heuristic cues rather than on actual success in the task. Subjective self-reports are also used in educational research on cognitive load,…
Descriptors: Metacognition, Self Efficacy, Self Evaluation (Individuals), Student Behavior
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Dumont, Émilie; Castellanos-Ryan, Natalie; Parent, Sophie; Jacques, Sophie; Séguin, Jean R.; Zelazo, Philip David – Developmental Science, 2022
Whereas accuracy is used as an indicator of cognitive flexibility in preschool-age children, reaction time (RT), or a combination of accuracy and RT, provide better indices of performance as children transition to school. Theoretical models and cross-sectional studies suggest that a speed-accuracy tradeoff may be operating across this transition,…
Descriptors: Foreign Countries, Preschool Children, Cognitive Ability, Reaction Time
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M. M. Elsherif; J. C. Catling – Scientific Studies of Reading, 2024
Purpose: Adults recognize words that are acquired during childhood more quickly than words acquired during adulthood. This is known as the Age of Acquisition (AoA) effect. The AoA effect, according to the integrated account, manifests in tasks necessitating greater semantic processing and in tasks with arbitrary input-output mapping. Compound…
Descriptors: Age Differences, Word Recognition, Linguistic Input, Reading Processes
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Lampe, Leonie F.; Hameau, Solène; Nickels, Lyndsey – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
This research investigated how word production is influenced by six feature-based semantic variables (number of semantic features, intercorrelational density, number of near semantic neighbors, semantic similarity, typicality, and distinctiveness). We simultaneously investigated effects of the six semantic variables on spoken picture naming in a…
Descriptors: Semantics, Naming, Pictorial Stimuli, Psycholinguistics
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Nagy, Gabriel; Ulitzsch, Esther – Educational and Psychological Measurement, 2022
Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Predictor Variables, Classification
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