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Obienu, A. C.; Amadin, F. I. – Education and Information Technologies, 2021
The continuing quest to ensure user acceptance is an ongoing management challenge and one that has occupied information systems researchers to such an extent that technology acceptance research is now considered to be among the more mature areas of exploration. Several models have been developed and validated in different contexts to help explain…
Descriptors: Adoption (Ideas), Educational Innovation, Usability, Models
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Al-Adwan, Ahmad Samed; Yaseen, Husam; Alsoud, Anas; Abousweilem, Fayrouz; Al-Rahmi, Waleed Mugahed – Education and Information Technologies, 2022
The key objective of this study was to reveal the key factors that impact university students' continued usage intentions with respect to Learning Management Systems (LMSs). Given the context-dependent nature of e-learning, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was applied and extended with constructs principally…
Descriptors: Integrated Learning Systems, Independent Study, College Students, Student Attitudes
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Polat, Özgül; Bayindir, Dilan – Early Child Development and Care, 2022
This study investigates the relations between school readiness and self-regulation skills of preschool children and parental involvement towards education of their preschool children. More specifically, we focused on the mediation role of preschoolers' self-regulation skills on the relation between parental involvement and school readiness. The…
Descriptors: Parent Participation, School Readiness, Correlation, Metacognition
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Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
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Sergio Dominguez-Lara; Mario A. Trógolo; Rodrigo Moreta-Herrera; Diego Vaca-Quintana; Manuel Fernández-Arata; Ana Paredes-Proaño – Journal of Psychoeducational Assessment, 2025
Academic engagement plays a crucial role in students' learning and performance. One of the most popular measures for assessing this construct is the Utrecht Work Engagement Scale for Students (UWES-S), which is based on a tridimensional conceptualization consisting of dedication, vigor, and absorption. However, prior research on its factor…
Descriptors: Learner Engagement, College Students, Foreign Countries, Factor Analysis
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Dan Wei; Peida Zhan; Hongyun Liu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…
Descriptors: Structural Equation Models, Goodness of Fit, Error of Measurement, Computation
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Chunhua Cao; Xinya Liang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Cross-loadings are common in multiple-factor confirmatory factor analysis (CFA) but often ignored in measurement invariance testing. This study examined the impact of ignoring cross-loadings on the sensitivity of fit measures (CFI, RMSEA, SRMR, SRMRu, AIC, BIC, SaBIC, LRT) to measurement noninvariance. The manipulated design factors included the…
Descriptors: Goodness of Fit, Error of Measurement, Sample Size, Factor Analysis
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Tenko Raykov – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…
Descriptors: Error of Measurement, Prerequisites, Factor Analysis, Evaluation Methods
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Darmawan Muttaqin – Journal of Psychoeducational Assessment, 2024
The Vocational Identity Status Assessment (VISA) is one of the instruments that can be used to assess vocational identity. Conceptually, VISA consists of six sub-dimensions and has been validated using factor analysis. This study provides a factor structure test of the Indonesian version of VISA using the exploratory structural equation modeling…
Descriptors: Foreign Countries, Structural Equation Models, Vocational Interests, Occupational Tests
Ayse Busra Ceviren – ProQuest LLC, 2024
Latent change score (LCS) models are a powerful class of structural equation modeling that allows researchers to work with latent difference scores that minimize measurement error. LCS models define change as a function of prior status, which makes it well-suited for modeling developmental theories or processes. In LCS models, like other latent…
Descriptors: Structural Equation Models, Error of Measurement, Statistical Bias, Monte Carlo Methods
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Serang, Sarfaraz – New Directions for Child and Adolescent Development, 2021
Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures…
Descriptors: Longitudinal Studies, National Surveys, Growth Models, Structural Equation Models
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Nestler, Steffen; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2022
The social relations model (SRM) is very often used in psychology to examine the components, determinants, and consequences of interpersonal judgments and behaviors that arise in social groups. The standard SRM was developed to analyze cross-sectional data. Based on a recently suggested integration of the SRM with structural equation models (SEM)…
Descriptors: Interpersonal Relationship, Longitudinal Studies, Data Analysis, Structural Equation Models
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Yuan Fang; Lijuan Wang – Grantee Submission, 2024
Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…
Descriptors: Structural Equation Models, Research Problems, Longitudinal Studies, Simulation
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Alem Amsalu; Sintayehu Belay – SAGE Open, 2024
The main goal of the current paper was to determine the effects of perceived school climate dimensions (leadership, relationships, professional learning-teaching climate, safety, and physical environment) on students' learning performance in upper primary schools. Correlational design consisted of structural equation modeling with mediation…
Descriptors: Educational Environment, Academic Achievement, Structural Equation Models, Elementary School Students
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Mauricio Garnier-Villarreal; Terrence D. Jorgensen – Grantee Submission, 2024
Model evaluation is a crucial step in SEM, consisting of two broad areas: global and local fit, where local fit indices are use to modify the original model. In the modification process, the modification index (MI) and the standardized expected parameter change (SEPC) are used to select the parameters that can be added to improve the fit. The…
Descriptors: Bayesian Statistics, Structural Equation Models, Goodness of Fit, Indexes
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