Language domains differentially predict mathematics performance in young children

Abstract

The purpose of this study was to examine the associations between child language ability and mathematics performance. First- and second-grade children (N = 365) were assessed on language ability and mathematics performance. Structural equation models revealed that receptive syntax and a broad screening tool significantly predicted math performance, while vocabulary did not. Path analyses corroborate these findings, with receptive syntax emerging as the only significant predictor of all indicators of mathematics performance. We conclude that syntax is a strong predictor of mathematics performance while vocabulary is not. Further, although many studies use receptive vocabulary to index language, it may not be the most predictive of or the best proxy for language ability in young children in the context of mathematics learning.