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Showing 1 to 15 of 77 results Save | Export
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Ori Ossmy; Danyang Han; Patrick MacAlpine; Justine Hoch; Peter Stone; Karen E. Adolph – Developmental Science, 2024
What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur only a negligible penalty. Behavioral data, however, cannot reveal whether a low penalty for falling…
Descriptors: Physical Activities, Robotics, Error Patterns, Infants
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Lee, Sooyong; Han, Suhwa; Choi, Seung W. – Educational and Psychological Measurement, 2022
Response data containing an excessive number of zeros are referred to as zero-inflated data. When differential item functioning (DIF) detection is of interest, zero-inflation can attenuate DIF effects in the total sample and lead to underdetection of DIF items. The current study presents a DIF detection procedure for response data with excess…
Descriptors: Test Bias, Monte Carlo Methods, Simulation, Models
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Journal of Educational Measurement, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
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Mangiulli, Ivan; Otgaar, Henry; Curci, Antonietta; Jelicic, Marko – Applied Cognitive Psychology, 2020
Research suggests that both internal (i.e., lying) and external (i.e., misinformation) factors can affect memory for a crime. We aimed to explore the effects of post-event misinformation on crime-related amnesia claims. We showed participants a mock crime and asked them to either simulate amnesia (simulators) or confess to it (confessors). Next,…
Descriptors: Deception, Memory, Crime, Recall (Psychology)
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Hoppe, Dorothée B.; Rij, Jacolien; Hendriks, Petra; Ramscar, Michael – Cognitive Science, 2020
Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers ("premarkers," e.g., gendered articles) or succeeding category markers ("postmarkers," e.g., gendered suffixes). Given that numerous…
Descriptors: Discrimination Learning, Computational Linguistics, Natural Language Processing, Artificial Languages
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Grantee Submission, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
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Sellberg, Charlott; Wiig, Astrid Camilla – Vocations and Learning, 2020
This study examines storytelling episodes in 13 video-recorded and fully transcribed post-simulation debriefings from a maritime navigation course. The aim is to scrutinize the facilitators' practice of telling stories from the sea during debriefings, to explore the organization and inner function of storytelling in debriefing. A combination of…
Descriptors: Marine Education, Story Telling, Navigation, Simulation
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Dong, Yixiao; Dumas, Denis; Clements, Douglas H.; Sarama, Julie – Journal of Experimental Education, 2023
Dynamic Measurement Modeling (DMM) is a recently-developed measurement framework for gauging developing constructs (e.g., learning capacity) that conventional single-timepoint tests cannot assess. The current project developed a person-specific DMM Trajectory Deviance Index (TDI) that captures the aberrance of an individual's growth from the…
Descriptors: Measurement Techniques, Simulation, Student Development, Educational Research
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Lee, Chansoon; Qian, Hong – Educational and Psychological Measurement, 2022
Using classical test theory and item response theory, this study applied sequential procedures to a real operational item pool in a variable-length computerized adaptive testing (CAT) to detect items whose security may be compromised. Moreover, this study proposed a hybrid threshold approach to improve the detection power of the sequential…
Descriptors: Computer Assisted Testing, Adaptive Testing, Licensing Examinations (Professions), Item Response Theory
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Robitzsch, Alexander; Lüdtke, Oliver – Large-scale Assessments in Education, 2023
One major aim of international large-scale assessments (ILSA) like PISA is to monitor changes in student performance over time. To accomplish this task, a set of common items (i.e., link items) is repeatedly administered in each assessment. Linking methods based on item response theory (IRT) models are used to align the results from the different…
Descriptors: Educational Trends, Trend Analysis, International Assessment, Achievement Tests
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Zhang, Zhonghua; Zhao, Mingren – Journal of Educational Measurement, 2019
The present study evaluated the multiple imputation method, a procedure that is similar to the one suggested by Li and Lissitz (2004), and compared the performance of this method with that of the bootstrap method and the delta method in obtaining the standard errors for the estimates of the parameter scale transformation coefficients in item…
Descriptors: Item Response Theory, Error Patterns, Item Analysis, Simulation
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Doleman, Brett; Freeman, Suzanne C.; Lund, Jonathan N.; Williams, John P.; Sutton, Alex J. – Research Synthesis Methods, 2020
This study aimed to determine for continuous outcomes dependent on baseline risk, whether funnel plot asymmetry may be due to statistical artefact rather than publication bias and evaluate a novel test to resolve this. Firstly, we conducted assessment for publication bias in nine meta-analyses of postoperative analgesics (344 trials with 25 348…
Descriptors: Outcomes of Treatment, Risk, Publications, Bias
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Wan, Tong; Doty, Constance M.; Geraets, Ashley A.; Saitta, Erin K. H.; Chini, Jacquelyn J. – International Journal of STEM Education, 2023
Background: In college science laboratory and discussion sections, student-centered active learning strategies have been implemented to improve student learning outcomes and experiences. Research has shown that active learning activities can increase student anxiety if students fear that they could be negatively evaluated by their peers. Error…
Descriptors: College Science, Science Laboratories, Student Centered Learning, Learning Strategies
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