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Understanding the complexities of mathematical cognition: a multi-level framework

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posted on 2023-08-24, 15:17 authored by Camilla GilmoreCamilla Gilmore
Mathematics skills are associated with future employment, well-being, and quality of life. However, many adults and children fail to learn the mathematics skills they require. To improve this situation, we need to have a better understanding of the processes of learning and performing mathematics. Over the past two decades, there has been a substantial growth in psychological research focusing on mathematics. However, to make further progress, we need to pay greater attention to the nature of, and multiple elements involved in, mathematical cognition. Mathematics is not a single construct; rather, overall mathematics achievement is comprised of proficiency with specific components of mathematics (e.g., number fact knowledge, algebraic thinking), which in turn recruit basic mathematical processes (e.g., magnitude comparison, pattern recognition). General cognitive skills and different learning experiences influence the development of each component of mathematics as well as the links between them. Here, I propose and provide evidence for a framework that structures how these components of mathematics fit together. This framework allows us to make sense of the proliferation of empirical findings concerning influences on mathematical cognition and can guide the questions we ask, identifying where we are missing both research evidence and models of specific mechanisms.

Funding

Royal Society Dorothy Hodgkin Fellowship

Research England, via the Centre for Mathematical Cognition

History

School

  • Science

Department

  • Mathematics Education Centre

Published in

Quarterly Journal of Experimental Psychology

Volume

76

Issue

9

Pages

1953-1972

Publisher

SAGE Publications

Version

  • VoR (Version of Record)

Rights holder

© Experimental Psychology Society

Publisher statement

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Acceptance date

2023-01-17

Publication date

2023-05-27

Copyright date

2023

ISSN

1747-0218

eISSN

1747-0226

Language

  • en

Depositor

Prof Camilla Gilmore. Deposit date: 30 May 2023

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