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Hsiu-Wen Yang; Christine Harradine; Chih-Ing Lim; Douglas H. Clements; Megan Vinh; Julie Sarama – Early Childhood Education Journal, 2025
Given the increased diversity of the population in the United States and the importance of early science, technology, engineering, and mathematics (STEM) learning, it is crucial to identify ways to reduce racial, ethnic, and gender disparities in STEM education. This is particularly important for children with disabilities with intersecting…
Descriptors: Demography, Early Intervention, STEM Education, Equal Education
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Hannah R. Thompson; Joni Ladawn Ricks-Oddie; Margaret Schneider; Sophia Day; Kira Argenio; Kevin Konty; Shlomit Radom-Aizik; Yawen Guo; Dan M. Cooper – Journal of School Health, 2025
Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…
Descriptors: Physical Fitness, Data Interpretation, Statistical Bias, Youth