Investigating Science Education Effect Sizes: Implications for Power Analyses and Programmatic Decisions

A priori power analyses allow researchers to estimate the number of participants needed to detect the effects of an intervention. However, power analyses are only as valid as the parameter estimates used. One such parameter, the expected effect size, can vary greatly depending on several study chara...

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Bibliographic Details
Published inAERA open Vol. 4; no. 3; pp. 233285841879199 - 233285841879217
Main Authors Taylor, Joseph A., Kowalski, Susan M., Polanin, Joshua R., Askinas, Karen, Stuhlsatz, Molly A. M., Wilson, Christopher D., Tipton, Elizabeth, Wilson, Sandra Jo
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.07.2018
Sage Publications Ltd
SAGE Publishing
Subjects
Computation
Educational Research
Effect Size
Intervention
Meta-analysis
Research Design
Researchers
Science Education
Statistical Analysis
meta-analysis
effect size
program evaluation
science education
student achievement
statistics
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Summary:A priori power analyses allow researchers to estimate the number of participants needed to detect the effects of an intervention. However, power analyses are only as valid as the parameter estimates used. One such parameter, the expected effect size, can vary greatly depending on several study characteristics, including the nature of the intervention, developer of the outcome measure, and age of the participants. Researchers should understand this variation when designing studies. Our meta-analysis examines the relationship between science education intervention effect sizes and a host of study characteristics, allowing primary researchers to access better estimates of effect sizes for a priori power analyses. The results of this meta-analysis also support programmatic decisions by setting realistic expectations about the typical magnitude of impacts for science education interventions.
ISSN:2332-8584
2332-8584
DOI:10.1177/2332858418791991