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Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Kasim, Adetayo – International Journal of Research & Method in Education, 2021
Educational researchers advocate the use of an effect size and its confidence interval to assess the effectiveness of interventions instead of relying on a p-value, which has been blamed for lack of reproducibility of research findings and the misuse of statistics. The aim of this study is to provide a framework, which can provide direct evidence…
Descriptors: Educational Research, Randomized Controlled Trials, Bayesian Statistics, Effect Size
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Kaplan, David; Huang, Mingya – Large-scale Assessments in Education, 2021
Of critical importance to education policy is monitoring trends in education outcomes over time. In the United States, the National Assessment of Educational Progress (NAEP) has provided long-term trend data since 1970; at the state/jurisdiction level, NAEP has provided long-term trend data since 1996. In addition to the national NAEP, all 50…
Descriptors: Educational Policy, Educational Trends, National Competency Tests, Bayesian Statistics
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Rehrig, Gwendolyn L.; Cheng, Michelle; McMahan, Brian C.; Shome, Rahul – Cognitive Research: Principles and Implications, 2021
A major problem in human cognition is to understand how newly acquired information and long-standing beliefs about the environment combine to make decisions and plan behaviors. Over-dependence on long-standing beliefs may be a significant source of suboptimal decision-making in unusual circumstances. While the contribution of long-standing beliefs…
Descriptors: Cognitive Processes, Decision Making, Semantics, Bayesian Statistics
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Binder, Karin; Krauss, Stefan; Schmidmaier, Ralf; Braun, Leah T. – Advances in Health Sciences Education, 2021
When physicians are asked to determine the positive predictive value from the a priori probability of a disease and the sensitivity and false positive rate of a medical test (Bayesian reasoning), it often comes to misjudgments with serious consequences. In daily clinical practice, however, it is not only important that doctors receive a tool with…
Descriptors: Clinical Diagnosis, Efficiency, Probability, Bayesian Statistics
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Frank Wang – Numeracy, 2021
In late November 2020, there was a flurry of media coverage of two companies' claims of 95% efficacy rates of newly developed COVID-19 vaccines, but information about the confidence interval was not reported. This paper presents a way of teaching the concept of hypothesis testing and the construction of confidence intervals using numbers announced…
Descriptors: COVID-19, Pandemics, Immunization Programs, Hypothesis Testing
Lauren Kennedy; Daniel Simpson; Andrew Gelman – Grantee Submission, 2019
Cognitive modelling shares many features with statistical modelling, making it seem trivial to borrow from the practices of robust Bayesian statistics to protect the practice of robust cognitive modelling. We take one aspect of statistical workflow--prior predictive checks--and explore how they might be applied to a cognitive modelling task. We…
Descriptors: Models, Cognitive Measurement, Experiments, Statistical Analysis
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Na Shan; Ping-Feng Xu – Journal of Educational and Behavioral Statistics, 2025
The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…
Descriptors: Bayesian Statistics, Item Response Theory, Adolescents, Longitudinal Studies
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Mikyung Shin; Jiyeon Park – Society for Research on Educational Effectiveness, 2025
Background: A single-case design focuses on individual performance and measures the causal relationships between variables (Kazdin, 2019). This experimental design enables researchers to measure the learning behaviors of individual participants over time across phases and assess the effectiveness of an instructional strategy in improving or…
Descriptors: Causal Models, Statistical Inference, Statistical Data, Research Design
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Mahmoud Abdi Tabari; Xinya Liang; Ágnes Albert – Studies in Second Language Learning and Teaching, 2025
Despite growing interest in task-based language teaching (TBLT), limited empirical work has examined how different rhetorical task types influence second language (L2) writing development, especially in relation to affective variables, such as writing anxiety. Existing research in TBLT has largely focused on cognitive dimensions, often neglecting…
Descriptors: Second Language Learning, Second Language Instruction, Teaching Methods, Writing (Composition)
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Kang, Jina; Baker, Ryan; Feng, Zhang; Na, Chungsoo; Granville, Peter; Feldon, David F. – Instructional Science: An International Journal of the Learning Sciences, 2022
Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered.…
Descriptors: Fundamental Concepts, Bayesian Statistics, Learning Processes, Research Skills
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Shi, Dingjing; Tong, Xin – Sociological Methods & Research, 2022
This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…
Descriptors: Bayesian Statistics, Monte Carlo Methods, Computer Software, Causal Models
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Mead, Alan D.; Zhou, Chenxuan – Journal of Applied Testing Technology, 2022
This study fit a Naïve Bayesian classifier to the words of exam items to predict the Bloom's taxonomy level of the items. We addressed five research questions, showing that reasonably good prediction of Bloom's level was possible, but accuracy varies across levels. In our study, performance for Level 2 was poor (Level 2 items were misclassified…
Descriptors: Artificial Intelligence, Prediction, Taxonomy, Natural Language Processing
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
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Zachary J. Roman; Patrick Schmidt; Jason M. Miller; Holger Brandt – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing…
Descriptors: Structural Equation Models, Bayesian Statistics, Response Style (Tests), Robustness (Statistics)
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Sedat Sen; Allan S. Cohen – Educational and Psychological Measurement, 2024
A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…
Descriptors: Goodness of Fit, Item Response Theory, Sample Size, Classification
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