2-115 - Underlying Executive Function Mechanisms for Math Learning

Session Type: Paper Symposium

Integrative Statement

Math ability in early childhood predicts math ability and overall academic achievement throughout the academic lifespan (Duncan et al., 2007). However, there is substantial individual differences in children’s early math skills. Executive function (EF) a construct comprised of inhibitory control, working memory, and cognitive flexibility appears to be of critical importance to children’s math ability, and is also related to children’s school readiness abilities more broadly (Blair, 2002; Blair & Razza, 2007; Bull & Lee, 2014). Using data collected from children age 3-9 in varying contexts in the US and UK, the proposed symposium explores the ways in which EF contributes to children’s early math ability. As a whole, these four presentations suggest that children’s EF is a domain general skill that supports mathematical cognition and math learning. The studies leverage longitudinal designs that feature both prospective and experimental methods. Specifically, they suggest a strong role for working memory and inhibitory control as underlying cognitive systems that supports children’s math ability. Findings suggest EF may be a suitable target for intervention to improve the math ability of young children and support the skills necessary to succeed in school. Ways in which academic instruction can benefit from these findings will be discussed.

Sub Unit

• Cognitive Processes

Chair

• Andrew Ribner, New York University

Individual Presentations

• Do Demands on Executive Function Enhance or Hinder Preschoolers’ Learning from a Math Game? - Presenting Author: Alana Foley, University of Chicago; Sarah H. Eason, University of Maryland; Sarah Leonard, University of Chicago; Kassie Kerr, University of Chicago; Amy Claessens, University of Chicago; Susan Levine, University of Chicago

• Direct and indirect influences of executive functions on mathematics achievement - Presenting Author: Camilla Gilmore, Loughborough University; Lucy Cragg, University of Nottingham

• Inhibitory Control and the Approximate Number System: Significant but Separate Predictors of Early Math Abilities - Presenting Author: Leanne Elliott, University of Pittsburgh; Melissa Libertus, University of Pittsburgh

• Executive Function Predicts Intercept in Math, but Predicts Negative Slope - Presenting Author: Andrew Ribner, New York University; Eric D. Finegood, New York University; Michael J Sulik, New York University; Clancy B. Blair, New York University