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Yangqiuting Li; Chandralekha Singh – Physical Review Physics Education Research, 2024
Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…
Descriptors: Structural Equation Models, Statistical Analysis, Educational Research, Causal Models
Peugh, James; Feldon, David F. – CBE - Life Sciences Education, 2020
Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the…
Descriptors: Structural Equation Models, Goodness of Fit, Statistical Analysis, Computation
Isiordia, Marilu; Ferrer, Emilio – Educational and Psychological Measurement, 2018
A first-order latent growth model assesses change in an unobserved construct from a single score and is commonly used across different domains of educational research. However, examining change using a set of multiple response scores (e.g., scale items) affords researchers several methodological benefits not possible when using a single score. A…
Descriptors: Educational Research, Statistical Analysis, Models, Longitudinal Studies
Sciffer, Michael G.; Perry, Laura B.; McConney, Andrew – British Journal of Sociology of Education, 2020
School socio-economic compositional (SEC) effects have been influential in educational research predicting a range of outcomes and influencing public policy. However, some recent studies have challenged the veracity of SEC effects when applying residualised-change and fixed effects models and simulating potential measurement errors in hierarchical…
Descriptors: School Demography, Socioeconomic Status, Socioeconomic Influences, Context Effect
Roorda, Debora L.; Jak, Suzanne; Zee, Marjolein; Oort, Frans J.; Koomen, Helma M. Y. – School Psychology Review, 2017
The present study took a meta-analytic approach to investigate whether students' engagement acts as a mediator in the association between affective teacher-student relationships and students' achievement. Furthermore, we examined whether results differed for primary and secondary school and whether similar results were found in a longitudinal…
Descriptors: Affective Behavior, Teacher Student Relationship, Longitudinal Studies, Meta Analysis
Zhou, Yuchun – International Education Studies, 2018
Since the 1980s when mixed methods emerged as "the third research methodology", it was widely adopted in Western countries. However, inadequate literature revealed how this methodology was accepted by scholars in Asian countries, such as China. Therefore, this paper used a quantitative survey to investigate Chinese scholars' perceptions…
Descriptors: Foreign Countries, Educational Research, Educational Researchers, Scholarship
Karakaya-Ozyer, Kubra; Aksu-Dunya, Beyza – International Journal of Research in Education and Science, 2018
Structural equation modeling (SEM) is one of the most popular multivariate statistical techniques in Turkish educational research. This study elaborates the SEM procedures employed by 75 educational research articles which were published from 2010 to 2015 in Turkey. After documenting and coding 75 academic papers, categorical frequencies and…
Descriptors: Literature Reviews, Structural Equation Models, Educational Technology, Multivariate Analysis
Green, Teegan – Studies in Higher Education, 2016
Despite increases in the number of articles published in higher education journals using structural equation modelling (SEM), research addressing their statistical sufficiency, methodological appropriateness and quantitative rigour is sparse. In response, this article provides a census of all covariance-based SEM articles published up until 2013…
Descriptors: Higher Education, Educational Research, Structural Equation Models, Sample Size
Blanchard, Rebecca D.; Konold, Timothy R. – Online Submission, 2011
This paper introduces latent growth modeling (LGM) as a statistical method for analyzing change over time in latent, or unobserved, variables, with particular emphasis of the application of this method in higher education research. While increasingly popular in other areas of education research and despite a wealth of publicly-available datasets…
Descriptors: Data Analysis, Statistical Analysis, Structural Equation Models, Higher Education
Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
Bodkin-Andrews, Gawaian; O'Rourke, Virginia; Craven, Rhonda G. – Australian Journal of Education, 2010
It is only relatively recently that empirical research has begun to emerge that has sought to further understand the factors that may contribute to the educational inequities between Indigenous Australian and non-Indigenous Australian students. Although it has been argued that research has typically employed small, unrepresentative case studies…
Descriptors: Educational Research, Self Concept, Educational Objectives, Outcomes of Education