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Donovan, Brian M. – Journal of Research in Science Teaching, 2017
For over a century, genetic arguments for the existence of racial inequality have been used to oppose policies that promote social equality. And, over that same time period, American biology textbooks have repeatedly discussed genetic differences between races. This experiment tests whether racial terminology in the biology curriculum causes…
Descriptors: Racial Bias, Labeling (of Persons), Science Curriculum, Biology
Brandon, Paul R.; Harrison, George M.; Lawton, Brian E. – American Journal of Evaluation, 2013
When evaluators plan site-randomized experiments, they must conduct the appropriate statistical power analyses. These analyses are most likely to be valid when they are based on data from the jurisdictions in which the studies are to be conducted. In this method note, we provide software code, in the form of a SAS macro, for producing statistical…
Descriptors: Statistical Analysis, Correlation, Effect Size, Benchmarking
Heemsoth, Tim; Heinze, Aiso – Journal of Experimental Education, 2016
Thus far, it is unclear how students can learn most effectively from their own errors. In this study, reflections on the rationale behind self-made errors are assumed to enhance knowledge acquisition. In a field experiment with pre/post/follow-up design, the authors practiced fractions with 174 seventh- and eighth-grade students who were randomly…
Descriptors: High School Students, Reflection, Error Patterns, Error Correction
Hedges, Larry V.; Hedberg, E. C. – Evaluation Review, 2013
Background: Cluster-randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Descriptors: Correlation, Multivariate Analysis, Educational Experiments, Statistical Analysis