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Oliver Lüdtke; Alexander Robitzsch – Journal of Experimental Education, 2025
There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…
Descriptors: Statistical Analysis, Longitudinal Studies, Error of Measurement, Hierarchical Linear Modeling
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Epameinondas Panagopoulos; Ioannis Kamarianos – Open Journal for Educational Research, 2025
This paper emphasizes the divergences in quantitative and qualitative methodological approaches when exploring trust relationships in school units. We focus on how participants responded and how the results were interpreted. This study, based on such design, questionnaires, and semi-structured interviews to understand trust among teachers and…
Descriptors: Statistical Analysis, Qualitative Research, Research Methodology, Trust (Psychology)
Shane Kelley – Sage Research Methods Cases, 2025
The research presented in this Case Study examines adjunct faculty satisfaction at an online public institution of higher education. Specifically, I analyzed student-, individual-, and institution-related factors of faculty satisfaction based on a previously constructed survey instrument found in the literature. While carrying out the research,…
Descriptors: Virtual Schools, College Faculty, Teacher Attitudes, Public Colleges
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Halil I. Tasova; Kevin C. Moore – Journal for Research in Mathematics Education, 2025
We examine the meanings students give to points when they are graphing relationships between quantities in dynamic, experiential contexts. Using data from teaching experiments with middle-grades students, we illustrate two main categories of meanings: iconic and quantitative. We then introduce four distinct subcategories of meanings: (a) iconic…
Descriptors: Middle School Students, Graphs, Middle School Mathematics, Statistical Analysis
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Youmi Suk; Chan Park; Chenguang Pan; Kwangho Kim – Society for Research on Educational Effectiveness, 2025
Objective: The current math course-taking plan for U.S. high school students is not optimized for all, with advanced math course participation skewed toward White and Asian students and varying across schools due to resources and policies (Dalton et al., 2007; Byun et al., 2015). These disparities widen achievement gaps and reduce STEM diversity.…
Descriptors: Secondary School Mathematics, Equal Education, Educational Policy, Advanced Courses
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Luke Keele; Matthew Lenard; Lindsay Page – Journal of Research on Educational Effectiveness, 2024
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Intervention, Cluster Grouping, Observation, Catholic Schools
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Amir Abdul Reda; Semuhi Sinanoglu; Mohamed Abdalla – Sociological Methods & Research, 2024
How can we measure the resource mobilization (RM) efforts of social movements on Twitter? In this article, we create the first ever measure of social movements' RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM…
Descriptors: Social Media, Social Action, Natural Language Processing, Politics
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Terry A. Beehr; Minseo Kim; Ian W. Armstrong – International Journal of Social Research Methodology, 2024
Previous research extensively studied reasons for and ways to avoid low response rates, but it largely ignored the primary research issue of the degree to which response rates matter, which we address. Methodological survey research on response rates has been concerned with how to increase responsiveness and with the effects of response rates on…
Descriptors: Surveys, Response Rates (Questionnaires), Effect Size, Research Methodology
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Qian Zhang; Qi Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In the article, we focused on the issues of measurement error and omitted confounders while conducting mediation analysis under experimental studies. Depending on informativeness of the confounders between the mediator (M) and outcome (Y), we described two approaches. When researchers are confident that primary confounders are included (e.g.,…
Descriptors: Error of Measurement, Research and Development, Mediation Theory, Causal Models
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Elayne P. Colón; Lori M. Dassa; Thomas M. Dana; Nathan P. Hanson – Action in Teacher Education, 2024
To meet accreditation expectations, teacher preparation programs must demonstrate their candidates are evaluated using summative assessment tools that yield sound, reliable, and valid data. These tools are primarily used by the clinical experience team -- university supervisors and mentor teachers. Institutional beliefs regarding best practices…
Descriptors: Student Teachers, Teacher Interns, Evaluation Methods, Interrater Reliability
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Michael B. Frisby – AERA Open, 2024
Education research has recently seen the emergence of two distinct frameworks guiding the application of quantitative methods through a more critical and equity-oriented lens. These two frameworks are critical quantitative (CritQuant) studies and quantitative critical race theory (QuantCrit). Although different in their intellectual traditions,…
Descriptors: Critical Theory, Statistical Analysis, Educational Research, Mathematics Education
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Judith Glaesser – International Journal of Social Research Methodology, 2024
Causal asymmetry is a situation where the causal factors under study are more suitable for explaining the outcome than its absence (or vice versa); they do not explain both equally well. In such a situation, presence of a cause leads to presence of the effect, but absence of the cause may not lead to absence of the effect. A conceptual discussion…
Descriptors: Comparative Analysis, Causal Models, Correlation, Foreign Countries
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Martin Hecht; Julia-Kim Walther; Manuel Arnold; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Planning longitudinal studies can be challenging as various design decisions need to be made. Often, researchers are in search for the optimal design that maximizes statistical power to test certain parameters of the employed model. We provide a user-friendly Shiny app OptDynMo available at https://shiny.psychologie.hu-berlin.de/optdynmo that…
Descriptors: Longitudinal Studies, Best Practices, Operating Expenses, Research Design
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Napol Rachatasumrit; Paulo F. Carvalho; Kenneth R. Koedinger – International Educational Data Mining Society, 2024
What does it mean for a model to be a better model? One conceptualization, indeed a common one in Educational Data Mining, is that a better model is the one that fits the data better, that is, higher prediction accuracy. However, oftentimes, models that maximize prediction accuracy do not provide meaningful parameter estimates, making them less…
Descriptors: Data Analysis, Models, Prediction, Accuracy
Ziqian Xu; Fei Gao; Anqi Fa; Wen Qu; Zhiyong Zhang – Grantee Submission, 2024
Conditional process models, including moderated mediation models and mediated moderation models, are widely used in behavioral science research. However, few studies have examined approaches to conduct statistical power analysis for such models and there is also a lack of software packages that provide such power analysis functionalities. In this…
Descriptors: Statistical Analysis, Sample Size, Mediation Theory, Monte Carlo Methods
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