Developmental Skills Linked to Math and Science Achievement
This project seeks to better understand, devise, and rapidly test interventions to support students’ foundational, developmental skills such as motivation, executive function, visuo-spatial skills, and phonological processing. This work builds on prior NSF-supported research on socio-demographic achievement gaps by proposing to (1) expand longitudinal data analyses of early developmental skills that are linked to later math/science, (2) strengthen the statistical methodology to include analysis at the math/science subscale level, (3) use latent profile analysis to cluster children with similar profiles and utilize growth models to predict 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 during the transition to school, and (6) formulate a comprehensive national strategy and priorities for addressing the skill deficits linked to math/science achievement gaps.
- Cameron, C. E., Grimm, K. J., Steele, J. S., Castro-Schilo, L., & Grissmer, D. W. (online 2014). Nonlinear Gompertz curve models of achievement gaps in reading and mathematics. Journal of Educational Psychology.
- Kim, H., Murrah, W. H., CAMERON, C. E., Brock, L. L., Cottone, E. A., & Grissmer, D. (2014). Psychometric properties of the teacher-reported Motor Skills Rating Scale. Journal of Psychoeducational Assessment.
- Kosovich, J. J., Hulleman, C. S., Barron, K. E., & Getty, S. (2014). A practical measure of student motivation: Establishing validity evidence for the expectancy-value-cost scale in middle school. Journal of Early Adolescence.
- Hulleman, C. S., & Barron, K. E. (In press). Motivation interventions in education: Bridging theory, research, and practice. To appear in: L. Corno & E. M. Anderman (Eds.), Handbook of Educational Psychology, 3rd Ed. (2016). Routledge, Taylor and Francis: New York, NY.
Project Dates: 8/15/2013-7/31/2018
Partners: Kevin Grimm, Arizona State University
Funding Source: National Science Foundation (NSF)