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Showing 1 to 15 of 24 results Save | Export
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Wendy Chan – Asia Pacific Education Review, 2024
As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…
Descriptors: Probability, Scores, Causal Models, Statistical Inference
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Lund, Thorleif – Scandinavian Journal of Educational Research, 2021
The purpose of this paper is to propose a revision of the well-known Campbellian system for causal research. The revised system, termed the COPS model, applies to both applied and basic research. Five validities are included, where two validities are adopted from the Campbellian system, and the validities are partly hierarchically ordered.…
Descriptors: Research, Validity, Causal Models, Measurement
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Charlotte Z. Mann; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2025
Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…
Descriptors: Causal Models, Statistical Analysis, Privacy, Risk
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Cheng, Patricia W.; Sandhofer, Catherine M.; Liljeholm, Mimi – Cognitive Science, 2022
The present paper examines a type of abstract domain-general knowledge required for the process of constructing useable domain-specific causal knowledge, the evident goal of causal learning. It tests the hypothesis that analytic knowledge of "causal-invariance decomposition functions" is essential for this process. Such knowledge…
Descriptors: Preschool Children, Learning Processes, Generalization, Heuristics
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Sarah E. Robertson; Jon A. Steingrimsson; Issa J. Dahabreh – Evaluation Review, 2024
When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with certain characteristics in order to improve trial economy or support inferences about subgroups of clusters, may preclude…
Descriptors: Randomized Controlled Trials, Generalization, Inferences, Hierarchical Linear Modeling
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Hertog, Steffen – Sociological Methods & Research, 2023
In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…
Descriptors: Case Studies, Generalization, Prediction, Mixed Methods Research
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Andrew P. Jaciw – American Journal of Evaluation, 2025
By design, randomized experiments (XPs) rule out bias from confounded selection of participants into conditions. Quasi-experiments (QEs) are often considered second-best because they do not share this benefit. However, when results from XPs are used to generalize causal impacts, the benefit from unconfounded selection into conditions may be offset…
Descriptors: Elementary School Students, Elementary School Teachers, Generalization, Test Bias
Kaplan, Avi; Cromley, Jennifer; Perez, Tony; Dai, Ting; Mara, Kyle; Balsai, Michael – Educational Researcher, 2020
In this commentary, we complement other constructive critiques of educational randomized control trials (RCTs) by calling attention to the commonly ignored role of context in causal mechanisms undergirding educational phenomena. We argue that evidence for the central role of context in causal mechanisms challenges the assumption that RCT findings…
Descriptors: Context Effect, Educational Research, Randomized Controlled Trials, Causal Models
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Goddu, Mariel K.; Gopnik, Alison – Developmental Psychology, 2020
Novel causal systems pose a problem of variable choice: How can a reasoner decide which variable is causally relevant? Which variable in the system should a learner manipulate to try to produce a desired, yet unfamiliar, casual outcome? In much causal reasoning research, participants learn how a particular set of preselected variables produce a…
Descriptors: Young Children, Causal Models, Logical Thinking, Inferences
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Daugirdiene, Ausra; Petrulyte, Aiste; Brandisauskiene, Agne – European Journal of Contemporary Education, 2018
The understanding and generalisation of causality are important thinking abilities, as they form the basis for a person's activity. Researchers exploring these abilities do not have a unified opinion regarding the age of children when they develop causative understanding and its determinant factors (e.g. age, prior knowledge, the content of a…
Descriptors: Young Children, Foreign Countries, Thinking Skills, Generalization
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Bao, Lei; Koenig, Kathleen; Xiao, Yang; Fritchman, Joseph; Zhou, Shaona; Chen, Cheng – Physical Review Physics Education Research, 2022
Abilities in scientific thinking and reasoning have been emphasized as core areas of initiatives, such as the Next Generation Science Standards or the College Board Standards for College Success in Science, which focus on the skills the future will demand of today's students. Although there is rich literature on studies of how these abilities…
Descriptors: Physics, Science Instruction, Teaching Methods, Thinking Skills
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Schneider, Carsten Q.; Rohlfing, Ingo – Sociological Methods & Research, 2016
Qualitative Comparative Analysis (QCA) is a method for cross-case analyses that works best when complemented with follow-up case studies focusing on the causal quality of the solution and its constitutive terms, the underlying causal mechanisms, and potentially omitted conditions. The anchorage of QCA in set theory demands criteria for follow-up…
Descriptors: Case Studies, Qualitative Research, Comparative Analysis, Causal Models
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Hitchcock, John H.; Kratochwill, Thomas R.; Chezan, Laura C. – Journal of Behavioral Education, 2015
A recent review of existing rubrics designed to help researchers evaluate the internal and external validity of single-case design (SCD) studies found that the various options yield consistent results when examining causal arguments. The authors of the review, however, noted considerable differences across the rubrics when addressing the…
Descriptors: Scoring Rubrics, Generalization, Research Methodology, Review (Reexamination)
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Maggin, Daniel M. – Journal of Behavioral Education, 2015
This paper responds to the commentary provided by Hitchcock et al. "(Journal of Behavioral Education," 2015) which provides updated information on the procedures for considering the generality of an intervention using the "What Works Clearinghouse" (WWC) single-case guidelines. The new information provided by Hitchcock et al.…
Descriptors: Scoring Rubrics, Generalization, Research Methodology, Review (Reexamination)
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Chan, Wendy – Journal of Research on Educational Effectiveness, 2017
Recent methods to improve generalizations from nonrandom samples typically invoke assumptions such as the strong ignorability of sample selection, which is challenging to meet in practice. Although researchers acknowledge the difficulty in meeting this assumption, point estimates are still provided and used without considering alternative…
Descriptors: Generalization, Inferences, Probability, Educational Research
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