National Science Foundation 1761012
Administered in: College of Education
Oral vocabulary difficulties before or soon after kindergarten are thought to result in reading difficulties during the primary grades, which in turn are thought to result in mathematics and science difficulties during the later elementary grades. To date, however, most empirical studies investigating the theorized inter-relations between oral vocabulary, reading, and mathematics and science difficulties have used small clinical or convenience samples of limited generalizability, included relatively few covariates, and examined the relations concurrently or only over short time periods. Thus, whether and to what extent oral vocabulary difficulties result in reading difficulties and, in turn, mathematics and science difficulties across the elementary grades in the U.S. is largely unknown. This project will examine the inter-relations between oral vocabulary, reading, mathematics, and science difficulties throughout the elementary grades, yielding greater scientific knowledge about the early onset and over-time dynamics of these types of learning difficulties. Doing so should help identify the cognitive, behavioral, affective, and social conditions that collectively interfere with STEM learning including early in children’s school careers. These analyses should also inform the delivery and design of STEM interventions at time periods when such interventions may be the most effective.
This project will analyze two nationally representative and longitudinal datasets (i.e., the Early Childhood Longitudinal Study-Birth Cohort and Kindergarten Cohort of 2011, or ECLS-B and ECLS-K:2011) to investigate risk factors for oral vocabulary difficulties prior to or by kindergarten. The team will also examine to what extent oral vocabulary and reading difficulties during kindergarten and 1st grade increase children’s risk of experiencing mathematics and science difficulties in later grades. To best address the project’s research aims, a range of advanced analytical methods will be used including multilevel modeling, latent growth and growth mixture modeling, and structural equation modeling with random and fixed effects.