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Showing 1 to 15 of 228 results Save | Export
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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
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Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
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Bixi Zhang; Wolfgang Wiedermann – Society for Research on Educational Effectiveness, 2022
Background: Studying causal effects is an important aim in education. Causal relationships indicate how well implements (e.g., interventions) work for the target subjects. A good strategy to get the inference in such relationships is to conduct randomized experiments. However, random assignment is limited in education research, even is discouraged…
Descriptors: Statistical Analysis, Causal Models, Algorithms, Simulation
Karun Adusumilli; Francesco Agostinelli; Emilio Borghesan – National Bureau of Economic Research, 2024
This paper examines the scalability of the results from the Tennessee Student-Teacher Achievement Ratio (STAR) Project, a prominent educational experiment. We explore how the misalignment between the experimental design and the econometric model affects researchers' ability to learn about the intervention's scalability. We document heterogeneity…
Descriptors: Class Size, Research Design, Educational Research, Program Effectiveness
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Heining Cham; Hyunjung Lee; Igor Migunov – Asia Pacific Education Review, 2024
The randomized control trial (RCT) is the primary experimental design in education research due to its strong internal validity for causal inference. However, in situations where RCTs are not feasible or ethical, quasi-experiments are alternatives to establish causal inference. This paper serves as an introduction to several quasi-experimental…
Descriptors: Causal Models, Educational Research, Quasiexperimental Design, Research Design
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Peter Schochet – Society for Research on Educational Effectiveness, 2024
Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
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Maksimovic, Jelena; Evtimov, Jelena – Research in Pedagogy, 2023
The paradigm on which a methodological approach is developed determines the situations in which its application will be most appropriate. The quantitative approach implies a positivist paradigm, the basis of which is cause-and-effect relationships, as well as the questioning and verifying of existing theories. Positivism aims to prove that…
Descriptors: Statistical Analysis, Research Methodology, Educational Research, Models
Nathan P. Helsabeck – ProQuest LLC, 2022
Assessing student achievement over multiple years is complicated by students' annual matriculation through different classrooms. The process of matriculation, or annual classroom change, threatens the validity of statistical inferences because it violates the independence of observations necessary in a regression context. The current study…
Descriptors: Growth Models, Academic Achievement, Student Promotion, Statistical Analysis
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
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García-Murillo, Gabriel; Novoa-Hernández, Pavel; Rodri?uez, Rocío Serrano – Interactive Learning Environments, 2023
In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better…
Descriptors: Learning Management Systems, College Students, Technology Uses in Education, Educational Research
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Raykov, Tenko; DiStefano, Christine – Educational and Psychological Measurement, 2021
The frequent practice of overall fit evaluation for latent variable models in educational and behavioral research is reconsidered. It is argued that since overall plausibility does not imply local plausibility and is only necessary for the latter, local misfit should be considered a sufficient condition for model rejection, even in the case of…
Descriptors: Goodness of Fit, Models, Educational Research, Behavioral Science Research
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Acevedo, Fernando – Journal of Education and Learning (EduLearn), 2023
In the last 40 years in much of the western world dropout rates in higher education have remained almost unchanged. Although student retention seems to be the most studied and discussed aspect, nearly every empirical study on the causes of dropout in higher education and even more the impact of retention actions carried out by universities, in…
Descriptors: Higher Education, Dropouts, Dropout Rate, Foreign Countries
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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
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Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation Methods
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Silva-Lugo, Jose L.; Warner, Laura A.; Galindo, Sebastian – Journal of Agricultural Education and Extension, 2022
Purpose: A literature research conducted in education and agricultural education journals published during a period of 10 years revealed that 98% of the studies used parametric analyses. In general, model assumptions were not tested, and statistical criteria were not followed to apply the parametric approach. The objective of this paper is to…
Descriptors: Agricultural Education, Nonparametric Statistics, Educational Research, Models
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