The goal of this project is to conduct a meta-analysis to assist in establishing a solid base of evidence to inform further research, practice, and policy in the area of early science education. The project will bring up-to-date the meta-analysis literature in the area of early science education.
A Quantitative Synthesis of Research on Elementary Science Programs
The success of all students in science has become a priority, as the economic future depends on a workforce that is capable in science, mathematics, technology, and engineering. One area of emphasis has been on elementary science, where children's early attitudes and orientations about science are formed. Given the growth of high-quality evaluations of elementary science programs in recent years and the need to know what works in science education, an up-to-date review identifying effective programs and malleable factors in elementary science is needed. The goal of this project is to conduct a meta-analysis to assist in establishing a solid base of evidence to inform further research, practice, and policy in the area of early science education. The previous meta-analysis completed by this team published findings from approximately ten years ago. This project will bring up-to-date the meta-analysis literature in the area of early science education.
The review methods in the proposed quantitative synthesis on elementary science programs will be similar to those used by the What Works Clearinghouse. The focus of the review procedures is on timeliness, comprehensiveness, transparency, and minimizing bias. The goal of the project is to obtain and synthesize the entire literature evaluating elementary science programs to discover what works, for whom, and under what conditions. The team will systematically review the literature available in English between 2010 and 2021 to locate every study that meets well-established and accepted standards. Second, studies are grouped by categories, to look for patterns among effect sizes across studies. The team will use meta-regression techniques to test statistical significance of the categories and will explore cross-cutting substantive and methodological factors, as well as key moderators and mediators. The team will communicate findings to many audiences, including scholarly journals, practitioner journals, and the public.