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Predictors of mathematics in primary school: Magnitude comparison, verbal and spatial working memory measures

The work

AuthorsSara Caviola; Lincoln John Colling; Irene C. Mammarella; Dénes Szűcs
Editors
Typearticle
Year2020
Citekeycaviola2020predictors

Where it appeared

Published inDevelopmental Science
PublisherWiley
Volume23
Issue6
Pagese12957

Identifiers

DOI10.1111/desc.12957
OpenAlexW3007936115

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Abstract

We determined the relative importance of the so-called approximate number system (ANS), symbolic number comparison (SNC) and verbal and spatial short-term and working memory (WM) capacity for mathematics achievement in 1,254 Grade 2, 4 and 6 children. The large sample size assured high power and low false report probability and allowed us to determine effect sizes precisely. We used reading decoding as a control outcome measure to test whether findings were specific to mathematics. Bayesian analysis allowed us to provide support for both null and alternative hypotheses. We found very weak zero-order correlations between ANS measures and math achievement. These correlations were not specific to mathematics, became non-significant once intelligence was considered and ANS measures were not selected as predictors of math by regression models. In contrast, overall SNC accuracy and spatial WM measures were reliable and mostly specific predictors of math achievement. Verbal short-term and WM and SNC reaction time were predictors of both reading and math achievement. We conclude that ANS tasks are not suitable as measures of math development in school-age populations. In contrast, all other cognitive functions we studied are promising markers of mathematics development.

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Cite it as

@article{caviola2020predictors,
  title        = {Predictors of mathematics in primary school: Magnitude comparison, verbal and spatial working memory measures},
  author       = {Sara Caviola and Lincoln John Colling and Irene C. Mammarella and Dénes Szűcs},
  year         = {2020},
  journal      = {Developmental Science},
  publisher    = {Wiley},
  volume       = {23},
  number       = {6},
  pages        = {e12957},
  doi          = {10.1111/desc.12957},
}

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