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Direct linkHannah 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
Kahn, Jennifer; Jiang, Shiyan – Learning, Media and Technology, 2021
We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using…
Descriptors: Visualization, Data Use, Data Interpretation, Decision Making
