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Chen, Dawn; Lu, Hongjing; Holyoak, Keith J. – Cognitive Science, 2017
A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…
Descriptors: Inferences, Abstract Reasoning, Learning Processes, Models
Marsman, Maarten; Wagenmakers, Eric-Jan – Educational and Psychological Measurement, 2017
P values have been critiqued on several grounds but remain entrenched as the dominant inferential method in the empirical sciences. In this article, we elaborate on the fact that in many statistical models, the one-sided "P" value has a direct Bayesian interpretation as the approximate posterior mass for values lower than zero. The…
Descriptors: Bayesian Statistics, Statistical Inference, Probability, Statistical Analysis
Levy, Roy – AERA Online Paper Repository, 2017
A conceptual distinction is drawn between indicators, which serve to define latent variables, and outcomes, which do not. However, commonly used frequentist and Bayesian estimation procedures do not honor this distinction. They allow the outcomes to influence the latent variables and the measurement model parameters for the indicators, rendering…
Descriptors: Bayesian Statistics, Structural Equation Models, Sampling, Goodness of Fit
Xing, Wanli; Li, Chenglu; Chen, Guanhua; Huang, Xudong; Chao, Jie; Massicotte, Joyce; Xie, Charles – Journal of Educational Computing Research, 2021
Integrating engineering design into K-12 curricula is increasingly important as engineering has been incorporated into many STEM education standards. However, the ill-structured and open-ended nature of engineering design makes it difficult for an instructor to keep track of the design processes of all students simultaneously and provide…
Descriptors: Engineering Education, Design, Feedback (Response), Student Evaluation
Linkow, Tamara; Miller, Hannah; Parsad, Amanda; Price, Cristofer; Martinez, Alina – National Center for Education Evaluation and Regional Assistance, 2021
These are the appendices for the report "Study of College Transition Messaging in GEAR UP: Impacts on Enrolling and Staying in College." Five appendices are included in the document: (1) Additional Details about College Transition Messaging; (2) Additional Information about How the Study Was Designed and Implemented; (3) Supplemental…
Descriptors: College Bound Students, College Freshmen, Telecommunications, Synchronous Communication
Bárcena, M. J.; Garín, M. A.; Martín, A.; Tusell, F.; Unzueta, A. – Journal of Statistics Education, 2019
Teaching some concepts in statistics greatly benefits from individual practice with immediate feedback. In order to provide such practice to a large number of students we have written a simulator based on an historical event: the loss in May 22, 1968, and subsequent search for the nuclear submarine USS Scorpion. Students work on a simplified…
Descriptors: Computer Simulation, Computer Assisted Instruction, Teaching Methods, Bayesian Statistics
Soltanlou, Mojtaba; Coldea, Andra; Artemenko, Christina; Ehlis, Ann-Christine; Fallgatter, Andreas J.; Nuerk, Hans-Christoph; Dresler, Thomas – Mind, Brain, and Education, 2019
It is under debate whether the neural representation of numbers and letters might rely on distinct neural correlates, or on a mostly shared neural network. In the present study, a total of 47 children in fifth grade (Experiment 1) and sixth grade (Experiment 2) simply copied numbers and letters on a touch screen while brain activation changes were…
Descriptors: Brain Hemisphere Functions, Spectroscopy, Numbers, Alphabets
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
Ossewaarde, Roelant; Jonkers, Roel; Jalvingh, Fedor; Bastiaanse, Roelien – Journal of Speech, Language, and Hearing Research, 2020
Purpose: Corpus analyses of spontaneous language fragments of varying length provide useful insights in the language change caused by brain damage, such as caused by some forms of dementia. Sample size is an important experimental parameter to consider when designing spontaneous language analyses studies. Sample length influences the confidence…
Descriptors: Speech Communication, Dementia, Computational Linguistics, Neurological Impairments
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
Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
Kleinberg, Bennett; Warmelink, Lara; Arntz, Arnoud; Verschuere, Bruno – Applied Cognitive Psychology, 2018
Verbal deception detection has gained momentum as a technique to tell truth-tellers from liars. At the same time, researchers' degrees of freedom make it hard to assess the robustness of effects. Replication research can help evaluate how reproducible an effect is. We present the first replication in verbal deception research whereby ferry…
Descriptors: Deception, Credibility, Verbal Communication, Bayesian Statistics
Casabianca, Jodi M.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2018
The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance--if the null hypothesis of "no DIF" is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical…
Descriptors: Test Bias, Hypothesis Testing, Bayesian Statistics, Statistical Analysis
Ames, Allison J. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior…
Descriptors: Bayesian Statistics, Item Response Theory, Statistical Inference, Prediction
Yuxi Qiu – ProQuest LLC, 2018
Research in education has become increasingly reliant on statistical modeling frameworks to be reflective of the subject matter, to accurately assess what students know and can do, to assist instructors with curriculum design by supplementing informative feedback, and to support policy-makers when making evidence-based decisions. A common feature…
Descriptors: Goodness of Fit, Learning Theories, Bayesian Statistics, Curriculum Design

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