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The cognitive and numerical predictors of early mathematical achievement: A latent growth curve analysis

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posted on 2025-04-23, 15:36 authored by Abbie Cahoon, Emine Simsek, Camilla GilmoreCamilla Gilmore, Victoria Simms

Longitudinal studies are essential for understanding causes of developmental change and growth rates of mathematical achievement. 128 UK-based children (Mage = 4 years; SDage = 3.3 months; age range 43–54 months; 70 female) were tracked for 15 months, from the beginning of preschool until the end of the first year of primary school (i.e., across 7 preschools to 18 primary schools) and were assessed at three-time points. At the beginning of preschool, data was collected from parents and children, including background demographics, domain-specific, domain-general, and language skills. Mathematical achievement was assessed once during preschool and at two time points during the first year of primary school. Using a latent growth model, we examined the contribution of the predictors to the growth patterns in mathematical achievement and the stability of initial individual differences during preschool to school transitions. Results showed that over a period of 15-months, children displayed substantial growth in mathematical achievement. This growth in mathematical achievement was linear and there was little variability in children’s rate of development. In contrast, there was substantial variance in initial mathematical achievement, and this variance was explained by children’s cardinality understanding and receptive vocabulary. These early variations highlight the importance of exposure to mathematical language and concepts in early childhood to ensure the development of broader mathematical skills.

Funding

Centre for Early Mathematics Learning

Economic and Social Research Council

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History

School

  • Science

Department

  • Mathematical Sciences

Published in

Journal of Cognition and Development

Publisher

Taylor & Francis (Routledge)

Version

  • VoR (Version of Record)

Rights holder

© Ulster University

Publisher statement

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Acceptance date

2024-11-18

Publication date

2024-12-22

Copyright date

2024

ISSN

1524-8372

eISSN

1532-7647

Language

  • en

Depositor

Prof Camilla Gilmore. Deposit date: 24 November 2024

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