Associations Between Young Children’s Flexible Attention to Numerical and Spatial Magnitudes and Early Math Skills
Year: 2025
Type: article
Study design: Observational Study
Abstract: Attending to numerical and spatial magnitude information is important for many math skills (e.g. measurement, proportional reasoning). The flexible attention to magnitudes (FAM) account proposes that preschool-aged children’s early ability to disentangle numerical and spatial magnitude information and flexibly shift attention between the two is a significant predictor of early math achievement. We recruited 226 children from diverse racial/ethnic and family income backgrounds in the Midwestern U.S. (51% female; Mage = 55 months; SDage = 8 months) to examine the associations between their FAM skill and math achievement. We first tested the hypothesis that children’s FAM skill is specific to their ability to flexibly shift between dimensions of both numerical and spatial magnitude. We did not find evidence that children were using a single-dimension strategy to complete the FAM task. We did find that children’s performance depended on which dimension they had previously attended to in prior trial levels, suggesting that the task indeed assesses children’s flexibly shifting between different dimensions of magnitudes. Second, we tested the association between FAM skill and math achievement while also taking into account proportional reasoning, number line estimation, subitizing, and nonsymbolic numerical magnitude comparison. We found that children’s FAM task performance was significantly related to their math achievement after controlling for demographic covariates, executive function (EF) skills, and specific math skills. Implications of these findings for understanding the development of early math skills for diverse preschool-aged children in the U.S. is discussed.
Authors: Mary C. Wagner, Marissa Brown, Molly K. Griffin, Mitchell Hanson, Danielle A. Barrett, Madelyn H. Hales, Julia R. Fabian
Institution: University of Dayton
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Award: G2793421185
OpenAlex ID: W4409458868
