Investigating Science Education Effect Sizes: Implications for Power Analyses and Programmatic Decisions
Year: 2018
Type: article
Study designs: Systematic Review, Meta-Analysis
Abstract: 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.
Source: AERA Open
Authors: Joseph A. Taylor, Susan M. Kowalski, Joshua R. Polanin, Karen Askinas, Molly A. M. Stuhlsatz, Christopher D. Wilson, Elizabeth Tipton, Sandra Jo Wilson
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,000
Funder: National Science Foundation
OpenAlex ID: W2886837267