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Edgar C. Merkle; Oludare Ariyo; Sonja D. Winter; Mauricio Garnier-Villarreal – Grantee Submission, 2023
We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…
Descriptors: Models, Bayesian Statistics, Correlation, Evaluation Methods
Daniel B. Wright – Open Education Studies, 2024
Pearson's correlation is widely used to test for an association between two variables and also forms the basis of several multivariate statistical procedures including many latent variable models. Spearman's [rho] is a popular alternative. These procedures are compared with ranking the data and then applying the inverse normal transformation, or…
Descriptors: Models, Simulation, Statistical Analysis, Correlation
Hansol Lee; Jang Ho Lee – Review of Educational Research, 2024
This study used a meta-analytic structural equation modeling approach to build extended versions of the simple view of reading (SVR) model in second and foreign language (SFL) learning contexts (i.e., SVR-SFL). Based on the correlation coefficients derived from primary studies, we replicated and integrated two previous extended meta-analytic SVR…
Descriptors: Second Language Learning, Reading, Decoding (Reading), Reading Comprehension
Oscar Blessed Deho; Lin Liu; Jiuyong Li; Jixue Liu; Chen Zhan; Srecko Joksimovic – IEEE Transactions on Learning Technologies, 2024
Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently,…
Descriptors: Learning Analytics, Ethics, Algorithms, Models
Herbert W. Marsh; Jiesi Guo; Reinhard Pekrun; Oliver Lüdtke; Fernando Núñez-Regueiro – Educational Psychology Review, 2024
Multi-wave-cross-lagged-panel models (CLPMs) of directional ordering are a focus of much controversy in educational psychology and more generally. Extending traditional analyses, methodologists have recently argued for including random intercepts and lag2 effects between non-adjacent waves and giving more attention to controlling covariates.…
Descriptors: Self Concept, Academic Achievement, Correlation, Educational Psychology
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2025
Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…
Descriptors: Correlation, Statistical Analysis, Models, Tests
Cortney DiRussa; Samantha Coyle-Eastwick; Britney Jeyanayagam – International Journal of Bullying Prevention, 2025
Bullying victimization is a school problem that warrants attention. While most work has focused on understanding bullies and victims, it is important that research explore how to promote bystander behavior during bullying as a mechanism to deter bullying in schools. Perceptions of the school climate may impact the likelihood of a student's…
Descriptors: Bullying, Intervention, Middle School Students, Prevention
Freddy Juarez; Jarred Pernier; Brittany Devies – New Directions for Student Leadership, 2024
This article shares the foundational leadership and organizational wellness (FLOW) model, which is a leadership development model that seeks to better understand the relationship between individual leadership development and organizational development and wellness. The model is presented as a whole, followed by deep exploration by each piece of…
Descriptors: Wellness, Organizational Culture, Leadership Training, Models
Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John – Educational and Psychological Measurement, 2021
This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates…
Descriptors: Goodness of Fit, Hierarchical Linear Modeling, Computation, Models
Craig J. Cullen; Lawrence Ssebaggala; Amanda L. Cullen – Mathematics Teacher: Learning and Teaching PK-12, 2024
In this article, the authors share their favorite "Construct It!" activity, which focuses on rate of change and functions. The initial approach to instruction was procedural in nature and focused on making use of formulas. Specifically, after modeling how to find the slope of the line given two points and use it to solve for the…
Descriptors: Models, Mathematics Instruction, Teaching Methods, Generalization
Benjamin Goecke; Paul V. DiStefano; Wolfgang Aschauer; Kurt Haim; Roger Beaty; Boris Forthmann – Journal of Creative Behavior, 2024
Automated scoring is a current hot topic in creativity research. However, most research has focused on the English language and popular verbal creative thinking tasks, such as the alternate uses task. Therefore, in this study, we present a large language model approach for automated scoring of a scientific creative thinking task that assesses…
Descriptors: Creativity, Creative Thinking, Scoring, Automation
Lu, Binwei – British Journal of Educational Studies, 2023
This study compares the estimated grammar school effect in different regression models, and explains why previous evidence of the effectiveness of grammar school is mixed. Like most studies of school effectiveness evaluation, previous research on grammar school effect usually applies regression to control for confounding between-school factors and…
Descriptors: Value Added Models, School Effectiveness, Academic Achievement, Comparative Analysis
Jianping Shen; Huang Wu – Educational Administration Quarterly, 2025
Principal leadership has been widely regarded as a powerful catalyst for school improvement and student learning. This article presents a multivariate meta-analysis of 42 empirical studies, published between 2000 and 2020, that examined the effects of principal leadership on student achievement in the United States. The focus is on the conceptual…
Descriptors: Principals, Leadership Styles, Academic Achievement, Correlation
Tenko Raykov; Lisa Calvocoressi; Randall E. Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
This paper is concerned with the process of selecting between the increasingly popular bi-factor model and the second-order factor model in measurement research. It is indicated that in certain settings widely used in empirical studies, the second-order model is nested in the bi-factor model and obtained from the latter after imposing appropriate…
Descriptors: Factor Analysis, Decision Making, Computer Software, Measurement Techniques