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Active CONTINUING GRANT National Science Foundation (US)

Early Childhood Science, Technology, and Engineering Education: A Meta-analysis of Learning and Teaching Innovations

$5.99M USD

Funder National Science Foundation (US)
Recipient Organization University of Connecticut
Country United States
Start Date Jul 15, 2022
End Date Jun 30, 2026
Duration 1,446 days
Number of Grantees 4
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2201889
Grant Description

Sociodemographic inequities in children's science skills are already evident in the early school grades, and early disparities may contribute to long-run gaps in children's persistence and outcomes in STEM. To disrupt the nation’s long- standing and substantial inequities in science education and careers, interventions to strengthen early science learning are critical.

This research synthesizes the cumulative impact of science, technology and engineering innovations on early childhood learning and attitudes, examining the roles that critical moderators play in classroom instruction. By building basic knowledge about the conditions under which innovations in early childhood science, technology, and engineering education are most supportive of children’s science learning, this research advances the goal of strengthening U.S. children’s future STEM attainment and the nation’s science competitiveness.

The completed meta-analytic synthesis provides researchers, practitioners, and policy makers with basic knowledge about the effectiveness of innovative approaches to early childhood science, technology, engineering education. In sum, the study develops knowledge that contributes to the national interest by conducting basic research on the effectiveness of approaches to science (technology, and engineering) instruction in early childhood.

In addition, this project produces an open-access, Web-based library of instrument information on all assessments that have been used in controlled studies of early childhood science, technology, and engineering education innovations. This repository allows researchers to build on existing assessment efforts and thereby support the accumulation of knowledge in the early childhood science, technology, and engineering domains.

The research project uses modern meta-analysis, a statistical modeling tool, to combine the results of multiple scientific studies about early childhood interventions on the learning of science, technology, and engineering in kindergarten and first grade. The statistical approach provides an estimate of the average effect across the interventions. Further, the meta-analytic approach allows for the identification of patterns across studies and the examination of sources of disagreement among the results, as well as an examination of interesting relationships across the accumulated set of studies.

In particular, the research examines patterns in what types of early childhood interventions work, for whom, and under what conditions.

This research project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad, and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development.

The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in STEM interest, education, learning and participation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

University of Connecticut

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