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Showing 1 to 15 of 17 results Save | Export
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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
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Leslie Rutkowski; David Rutkowski – Journal of Creative Behavior, 2025
The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…
Descriptors: Creativity, Creative Thinking, Measurement, Sampling
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Kenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy
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Chen, Li-Ting; Andrade, Alejandro; Hanauer, Matthew James – AERA Online Paper Repository, 2017
Single-case design is a repeated-measures research approach for the study of the effect of an intervention, and its importance is increasingly being recognized in education and psychology. We propose a Bayesian approach for estimating intervention effects in SCD. A Bayesian inference does not rely on large sample theories and thus is particularly…
Descriptors: Bayesian Statistics, Research Design, Case Studies, Intervention
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Motz, Benjamin A.; Carvalho, Paulo F.; de Leeuw, Joshua R.; Goldstone, Robert L. – Journal of Learning Analytics, 2018
To identify the ways teachers and educational systems can improve learning, researchers need to make causal inferences. Analyses of existing datasets play an important role in detecting causal patterns, but conducting experiments also plays an indispensable role in this research. In this article, we advocate for experiments to be embedded in real…
Descriptors: Causal Models, Statistical Inference, Inferences, Educational Experiments
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VanHoudnos, Nathan M.; Greenhouse, Joel B. – Journal of Educational and Behavioral Statistics, 2016
When cluster randomized experiments are analyzed as if units were independent, test statistics for treatment effects can be anticonservative. Hedges proposed a correction for such tests by scaling them to control their Type I error rate. This article generalizes the Hedges correction from a posttest-only experimental design to more common designs…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Error of Measurement, Scaling
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Gu, Fei; Preacher, Kristopher J.; Ferrer, Emilio – Journal of Educational and Behavioral Statistics, 2014
Mediation is a causal process that evolves over time. Thus, a study of mediation requires data collected throughout the process. However, most applications of mediation analysis use cross-sectional rather than longitudinal data. Another implicit assumption commonly made in longitudinal designs for mediation analysis is that the same mediation…
Descriptors: Statistical Analysis, Models, Research Design, Case Studies
Gelman, Andrew; Imbens, Guido – National Bureau of Economic Research, 2014
It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…
Descriptors: Regression (Statistics), Mathematical Models, Causal Models, Research Methodology
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Eide, Eric R.; Showalter, Mark H. – Economics of Education Review, 2012
Professors Richard J. Murnane and John B. Willett set out to capitalize on recent developments in education data and methodology by attempting to answer the following questions: How can new methods and data be applied most effectively in educational and social science research? What kinds of research designs are most appropriate? What kinds of…
Descriptors: Social Science Research, Research Methodology, Audiences, Usability
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Larwin, Karen H.; Larwin, David A. – Journal of Education for Business, 2011
Bootstrapping methods and random distribution methods are increasingly recommended as better approaches for teaching students about statistical inference in introductory-level statistics courses. The authors examined the effect of teaching undergraduate business statistics students using random distribution and bootstrapping simulations. It is the…
Descriptors: Experimental Groups, Control Groups, Research Design, Grade Point Average
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Bonett, Douglas G. – Psychological Methods, 2009
L. Wilkinson and the Task Force on Statistical Inference (1999) recommended reporting confidence intervals for measures of effect sizes. If the sample size is too small, the confidence interval may be too wide to provide meaningful information. Recently, K. Kelley and J. R. Rausch (2006) used an iterative approach to computer-generate tables of…
Descriptors: Intervals, Sample Size, Effect Size, Statistical Inference
Rickles, Jordan H. – Society for Research on Educational Effectiveness, 2010
This paper illustrates how information collected through interviews can develop a richer understanding of the assignment mechanism, which can result in more plausible causal effect estimates from observational studies and provides a roadmap for sensitivity analysis. Focusing on the issue of assignment to algebra in 8th grade, the author shows how…
Descriptors: Middle Schools, Grade 8, Interviews, Algebra
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Serlin, Ronald C. – Psychological Methods, 2010
The sense that replicability is an important aspect of empirical science led Killeen (2005a) to define "p[subscript rep]," the probability that a replication will result in an outcome in the same direction as that found in a current experiment. Since then, several authors have praised and criticized 'p[subscript rep]," culminating…
Descriptors: Epistemology, Effect Size, Replication (Evaluation), Measurement Techniques
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Davison, Mark L.; Sharma, Anu R. – Psychometrika, 1994
Three analyses of pretest and posttest data are considered: (1) posttest only designs; (2) two-way repeated measures of analysis of variance (ANOVA); and (3) one-way analysis of covariance (ANCOVA). Conditions that ensure legitimacy of inferences about the equality of treatment effects on the latent variable theta are discussed. (SLD)
Descriptors: Analysis of Covariance, Analysis of Variance, Pretests Posttests, Research Design
Kish, Leslie – 1989
A brief, practical overview of "design effects" (DEFFs) is presented for users of the results of sample surveys. The overview is intended to help such users to determine how and when to use DEFFs and to compute them correctly. DEFFs are needed only for inferential statistics, not for descriptive statistics. When the selections for…
Descriptors: Computer Software, Error of Measurement, Mathematical Models, Research Design
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