Literature DB >> 28432933

(Non-)symbolic magnitude processing in children with mathematical difficulties: A meta-analysis.

Christin Schwenk1, Delphine Sasanguie2, Jörg-Tobias Kuhn3, Sophia Kempe4, Philipp Doebler5, Heinz Holling6.   

Abstract

Symbolic and non-symbolic magnitude representations, measured by digit or dot comparison tasks, are assumed to underlie the development of arithmetic skills. The comparison distance effect (CDE) has been suggested as a hallmark of the preciseness of mental magnitude representations. It implies that two magnitudes are harder to discriminate when the numerical distance between them is small, and may therefore differ in children with mathematical difficulties (MD), i.e. low mathematical achievement or dyscalculia. However, empirical findings on the CDE in children with MD are heterogeneous, and only few studies assess both symbolic and non-symbolic skills. This meta-analysis therefore integrates 44 symbolic and 48 non-symbolic response time (RT) outcomes reported in nineteen studies (N=1630 subjects, aged 6-14 years). Independent of age, children with MD show significantly longer mean RTs than typically achieving controls, particularly on symbolic (Hedges' g=0.75; 95% CI [0.51; 0.99]), but to a significantly lower extent also on non-symbolic (g=0.24; 95% CI [0.13; 0.36]) tasks. However, no group differences were found for the CDE. Extending recent work, these meta-analytical findings on children with MD corroborate the diagnostic importance of magnitude comparison speed in symbolic tasks. By contrast, the validity of CDE measures in assessing MD is questioned.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Developmental dyscalculia; Distance effect; Mathematical difficulties; Meta-analysis; Non-symbolic magnitude comparison; Symbolic magnitude comparison

Mesh:

Year:  2017        PMID: 28432933     DOI: 10.1016/j.ridd.2017.03.003

Source DB:  PubMed          Journal:  Res Dev Disabil        ISSN: 0891-4222


  8 in total

1.  Predicting Mathematical Learning Difficulties Using Fundamental Calculative Ability Test (FCAT).

Authors:  Sawako Ohba; Tatsuya Koeda; Masayoshi Oguri; Tohru Okanishi; Yoshihiro Maegaki
Journal:  Yonago Acta Med       Date:  2022-08-29       Impact factor: 1.371

2.  University students with attention deficit hyperactivity disorder (ADHD): a consensus statement from the UK Adult ADHD Network (UKAAN).

Authors:  Jane A Sedgwick-Müller; Ulrich Müller-Sedgwick; Marios Adamou; Marco Catani; Rebecca Champ; Gísli Gudjónsson; Dietmar Hank; Mark Pitts; Susan Young; Philip Asherson
Journal:  BMC Psychiatry       Date:  2022-04-22       Impact factor: 4.144

3.  How Cognitive Strengths Compensate Weaknesses Related to Specific Learning Difficulties in Fourth-Grade Children.

Authors:  Marije D E Huijsmans; Tijs Kleemans; Evelyn H Kroesbergen
Journal:  Front Psychol       Date:  2021-02-24

4.  The Cognitive Profile of Math Difficulties: A Meta-Analysis Based on Clinical Criteria.

Authors:  Stefan Haberstroh; Gerd Schulte-Körne
Journal:  Front Psychol       Date:  2022-03-11

Review 5.  Iconic Mathematics: Math Designed to Suit the Mind.

Authors:  Peter Kramer
Journal:  Front Psychol       Date:  2022-06-13

6.  Dyscalculia and Typical Math Achievement Are Associated With Individual Differences in Number-Specific Executive Function.

Authors:  Eric D Wilkey; Courtney Pollack; Gavin R Price
Journal:  Child Dev       Date:  2018-12-31

Review 7.  Innate or Acquired? - Disentangling Number Sense and Early Number Competencies.

Authors:  Julia Siemann; Franz Petermann
Journal:  Front Psychol       Date:  2018-04-19

Review 8.  Developmental brain dynamics of numerical and arithmetic abilities.

Authors:  Stephan E Vogel; Bert De Smedt
Journal:  NPJ Sci Learn       Date:  2021-07-23
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.