Evidence map›Paper›PMID 34244592›Full record

ArticleScientific reports2021

Perception of geometric sequences and numerosity both predict formal geometric competence in primary school children.

Elisa Castaldi, Roberto Arrighi, Guido M Cicchini, Arianna Andolfi, Giuseppe Maduli, David C Burr, Giovanni Anobile

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Elisa Castaldi *Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126, Pisa, Italy.
Roberto Arrighi *Department of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, 50139, Florence, Italy. roberto.arrighi@gmail.com.
Guido M CicchiniCNR Neuroscience Institute, 56100, Pisa, Italy.
Arianna AndolfiDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, 50139, Florence, Italy.
Giuseppe MaduliDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, 50139, Florence, Italy.
David C BurrDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, 50139, Florence, Italy.
Giovanni AnobileDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, 50139, Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While most animals have a sense of number, only humans have developed symbolic systems to describe and organize mathematical knowledge. Some studies suggest that human arithmetical knowledge may be rooted in an ancient mechanism dedicated to perceiving numerosity, but it is not known if formal geometry also relies on basic, non-symbolic mechanisms. Here we show that primary-school children who spontaneously detect and predict geometrical sequences (non-symbolic geometry) perform better in school-based geometry tests indexing formal geometric knowledge. Interestingly, numerosity discrimination thresholds also predicted and explained a specific portion of variance of formal geometrical scores. The relation between these two non-symbolic systems and formal geometry was not explained by age or verbal reasoning skills. Overall, the results are in line with the hypothesis that some human-specific, symbolic systems are rooted in non-symbolic mechanisms.

Indexed as

MathematicsChildCognitionFemaleHumansMaleMathematical ConceptsPattern Recognition, VisualProblem SolvingSchoolsVisual Perception

Identifiers

PMID34244592
PMCPMC8271001

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.