"Developmental skills linked to math and science achievement: An interdisciplinary data-intensive approach to identification and improvement through experimental intervention" is a 5-year project of the Research and Evaluation on Education in Science and Engineering (REESE) program to better understand and devise (and test) interventions to address deficits in foundational skills that the investigators hypothesize may help to close racial/SES and international gaps in math and science. The hypotheses suggest that deficits in certain early skills underlie a significant proportion of racial/SES math and science gaps, and the large proportion (about one-half) of U.S. students with significant skill gaps underlies a significant part of mediocre international math/science scores. This work builds on prior NSF-supported research. Goals of the proposed research are to: (1) expand longitudinal data sets used to identify and characterize the developmental skills linked to later math/science, (2) strengthen the statistical methodology used to link early developmental skills to later achievement and incorporate analysis at the math/science subscale level, (3) introduce a new statistical methodology - latent profile analysis - to cluster children using their multiple skill distributions into groups with similar profiles and utilize growth models to predict their achievement trajectories as skills change, (4) formalize and shorten the process involved in the design, development and experimental testing of interventions, (5) develop strategies for combining interventions and using multiple interventions for a cohort of children from preschool to early grades that would eliminate achievement gaps, and (6) formulate a comprehensive national strategy and priorities for addressing the skill deficits linked to math/science achievement gaps.

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University of Virginia
United States
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