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Selcuk Acar; Emel Cevik; Emily Fesli; Rumeysa Nalan Bozkurt; James C. Kaufman – Journal of Creative Behavior, 2024
Domain-specificity is a topic of debate within the field of creativity. To shed light on this issue, we conducted a meta-analysis of cross-domain correlations based on the Kaufman Domains of Creativity Scale (K-DOCS). To evaluate the model fit of one general factor versus two factors that encompass the primary K-DOCS subscales (Scholarly,…
Descriptors: Creativity, Science Education, Meta Analysis, Structural Equation Models
Lennert J. Groot; Kees-Jan Kan; Suzanne Jak – Research Synthesis Methods, 2024
Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…
Descriptors: Meta Analysis, Structural Equation Models, Research Methodology, Data Analysis
Caleb Or – OTESSA Journal, 2024
This study uses one-step meta-analytic structural equation modelling to delve into the technology acceptance model's (TAM) application within education, assessing perceived usefulness, ease of use, intentions to use, and actual technology use. It synthesises previous findings to validate the TAM's effectiveness and uncover the model's predictive…
Descriptors: Literature Reviews, Meta Analysis, Technology Integration, Educational Technology
Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
In'nami, Yo; Cheung, Mike W.-L.; Koizumi, Rie; Wallace, Matthew P. – Language Learning, 2023
Second language (L2) listening comprehension is a function of many variables. We focused on metacognitive awareness, which we measured using the Metacognitive Awareness Listening Questionnaire (MALQ; Vandergrift et al., 2006), and meta-analyzed (a) the factor structure of the MALQ and (b) the relationship between metacognitive awareness and L2…
Descriptors: Second Language Learning, Listening Comprehension, Metacognition, Meta Analysis
Sayed Masood Haidari; Ayhan Koçoglu; Sedat Kanadli – Journal on Efficiency and Responsibility in Education and Science, 2023
This meta-analysis examined whether motivation mediated the relationship between self-efficacy, locus of control, and academic achievement. Thirty-seven studies providing correlation estimates for 40 different samples were included in the analysis. The data from these studies were fitted to three models using a two-stage structural equation…
Descriptors: Locus of Control, Self Efficacy, Student Motivation, Academic Achievement
Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2021
Network meta-analysis (NMA) compares the efficacy and harm between several treatments by combining direct and indirect evidence. The validity of NMA requires that all available evidence form a coherent network. Failure to meet such requirement is known as inconsistency. The most popular approach to inconsistency detection is to compare the direct…
Descriptors: Networks, Meta Analysis, Evidence, Evaluation Methods
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
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Grantee Submission, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Jak, Suzanne; Li, Hongli; Kolbe, Laura; Jonge, Hannelies; Cheung, Mike W.-L. – Research Synthesis Methods, 2021
Meta-analytic structural equation modeling (MASEM) refers to fitting structural equation models (SEMs) (such as path models or factor models) to meta-analytic data. Currently, fitting MASEMs may be challenging for researchers that are not accustomed to working with R software and packages. Therefore, we developed webMASEM; a web application for…
Descriptors: Meta Analysis, Structural Equation Models, Tutorial Programs, Computer Oriented Programs
Or, Caleb – International Journal of Technology in Education and Science, 2023
The Unified Theory of Technology and Use of Technology (UTAUT) has been widely used in information system studies since its introduction in 2003. The current study synthesizes 40 empirical studies based on UTAUT in educational contexts using the one-stage meta-analytic structural equation modelling method. While the study confirmed the initial…
Descriptors: Technology Uses in Education, Educational Technology, Information Systems, Meta Analysis
Ashley Hannah Majzun – ProQuest LLC, 2023
Meta-analytic Structural Equation Modeling (MASEM) is the combination of meta-analysis (MA) and structural equation modeling (SEM). With new MASEM methodologies developed over the past few years, there is an opportunity to compare the past approaches with the new ones. The purpose of this dissertation is two-fold. First, the parameter estimates,…
Descriptors: Meta Analysis, Structural Equation Models, College Students, Academic Persistence
Ünal, Zehra E.; Greene, Nathaniel R.; Lin, Xin; Geary, David C. – Educational Psychology Review, 2023
Two meta-analyses assessed whether the relations between reading and mathematics outcomes could be explained through overlapping skills (e.g., systems for word and fact retrieval) or domain-general influences (e.g., top-down attentional control). The first (378 studies, 1,282,796 participants) included weighted random-effects meta-regression…
Descriptors: Correlation, Reading Achievement, Mathematics Achievement, Meta Analysis
Kanadli, Sedat; Arslantas, Haci Ismail; Inandi, Yusuf – Asia Pacific Education Review, 2023
In the literature, there are a great number of primary studies that examine the relationship between professional burnout, job satisfaction, and life satisfaction of education workers and that do not have consistent results. The aim of this study is to establish a model that will explain the life satisfaction of education workers by determining…
Descriptors: Predictor Variables, Life Satisfaction, Teacher Attitudes, Foreign Countries