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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Chantelle Gray – Educational Philosophy and Theory, 2025
In contemporary societies, the processes of transindividuation by which knowledges are transformed into cycles and rhythms of metastability have been dramatically short-circuited. In turn, this has provoked the spiritual misery and pseudo-fabulations so prevalent all around us, including our educational contexts. For Stiegler, this is nothing…
Descriptors: Educational Philosophy, Electronic Learning, Automation, Educational Theories
Jianbin Fu; TsungHan Ho; Xuan Tan – Practical Assessment, Research & Evaluation, 2025
Item parameter estimation using an item response theory (IRT) model with fixed ability estimates is useful in equating with small samples on anchor items. The current study explores the impact of three ability estimation methods (weighted likelihood estimation [WLE], maximum a posteriori [MAP], and posterior ability distribution estimation [PST])…
Descriptors: Item Response Theory, Test Items, Computation, Equated Scores
Francesco Poli; Marlene Meyer; Rogier B. Mars; Sabine Hunnius – Child Development, 2025
Humans are driven by an intrinsic motivation to learn, but the developmental origins of curiosity-driven exploration remain unclear. We investigated the computational principles guiding 4-year-old children's exploration during a touchscreen game (N = 102, F = 49, M = 53, primarily white and middle-class, data collected in the Netherlands from…
Descriptors: Foreign Countries, Young Children, Learning Motivation, Discovery Learning
Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
Jeff Coon; Paulina N. Silva; Alexander Etz; Barbara W. Sarnecka – Journal of Cognition and Development, 2025
Bayesian methods offer many advantages when applied to psychological research, yet they may seem esoteric to researchers who are accustomed to traditional methods. This paper aims to lower the barrier of entry for developmental psychologists who are interested in using Bayesian methods. We provide worked examples of how to analyze common study…
Descriptors: Developmental Psychology, Bayesian Statistics, Research Methodology, Psychological Studies
Jean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
Milica Miocevic; Fayette Klaassen; Mariola Moeyaert; Gemma G. M. Geuke – Journal of Experimental Education, 2025
Mediation analysis in Single Case Experimental Designs (SCEDs) evaluates intervention mechanisms for individuals. Despite recent methodological developments, no clear guidelines exist for maximizing power to detect the indirect effect in SCEDs. This study compares frequentist and Bayesian methods, determining (1) minimum required sample size to…
Descriptors: Research Design, Mediation Theory, Statistical Analysis, Simulation
Yasuhiro Yamamoto; Yasuo Miyazaki – Journal of Experimental Education, 2025
Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…
Descriptors: Sample Size, Hierarchical Linear Modeling, Bayesian Statistics, Prior Learning
Ming-Chi Tseng – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within x within and between x within latent interaction under the CLPM model framework is compared between the one-step Bayesian LMS method and the two-step multiple imputation analysis through a simulation…
Descriptors: Guidelines, Bayesian Statistics, Self Esteem, Depression (Psychology)
Kazuhiro Yamaguchi – Journal of Educational and Behavioral Statistics, 2025
This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…
Descriptors: Models, Classification, Bayesian Statistics, Evaluation Methods
Alex Tabarrok – Journal of Economic Education, 2025
During the pandemic, the economic way of thinking was extraordinarily useful, leading to a quick consensus among economists of widely differing political persuasions on many issues of pandemic policy. Yet speaking to politicians, bureaucrats, and the public revealed many ways in which the economic way of thinking was foreign and sometimes…
Descriptors: COVID-19, Pandemics, Economics, Economics Education
Joseph A. Rios; Jiayi Deng – Educational and Psychological Measurement, 2025
To mitigate the potential damaging consequences of rapid guessing (RG), a form of noneffortful responding, researchers have proposed a number of scoring approaches. The present simulation study examines the robustness of the most popular of these approaches, the unidimensional effort-moderated (EM) scoring procedure, to multidimensional RG (i.e.,…
Descriptors: Scoring, Guessing (Tests), Reaction Time, Item Response Theory
Anirudhan Badrinath; Zachary Pardos – Journal of Educational Data Mining, 2025
Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Problem Solving, Audience Response Systems
Xiaojuan Zhang; Bing Cheng; Yu Zou; Yang Zhang – Journal of Speech, Language, and Hearing Research, 2025
Purpose: This meta-analysis study aimed to determine the optimal level of talker variability in training to maximize second-language speech learning. Method: We conducted a systematic search for studies comparing different levels of talker variability in nonnative speech training, published through July 2024. Two independent reviewers screened…
Descriptors: Meta Analysis, Bayesian Statistics, Second Language Learning, Language Acquisition
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