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Joshua Weidlich; Ben Hicks; Hendrik Drachsler – Educational Technology Research and Development, 2024
Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today,…
Descriptors: Educational Research, Educational Technology, Research Design, Structural Equation Models
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
Xu Qin; Lijuan Wang – Grantee Submission, 2023
Research questions regarding how, for whom, and where a treatment achieves its effect on an outcome have become increasingly valued in substantive research. Such questions can be answered by causal moderated mediation analysis, which assesses the heterogeneity of the mediation mechanism underlying the treatment effect across individual and…
Descriptors: Causal Models, Mediation Theory, Computer Software, Statistical Analysis
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Yu, Chong Ho – 2002
This paper asserts that causality is an intriguing but controversial topic in philosophy, statistics, and educational and psychological research. By supporting the Causal Markov Condition and the faithfulness condition, Clark Glymour attempted to draw causal inferences from structural equation modeling. According to Glymour, in order to make…
Descriptors: Causal Models, Markov Processes, Probability, Statistical Inference
Holland, Paul W. – 1988
D. B. Rubin's model for causal inference in experiments and observational studies is enlarged to analyze the problem of "causes causing causes" and is compared to path analysis and recursive structural equations models. A special quasiexperimental design, the encouragement design, is used to give concreteness to the discussion by…
Descriptors: Causal Models, Observation, Path Analysis, Quasiexperimental Design