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How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?

Predictions begin with an extrapolation of the properties of their underlying representations to forecast a future state not presently in evidence. For numerical predictions, sets of numbers are summarized and the result forms the basis of and constrains numerical predictions. One open question is h...

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Autores principales: Morris, Bradley J., Todaro, Rachael, Arner, Tracy, Roche, Jennifer M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241830/
https://www.ncbi.nlm.nih.gov/pubmed/35783810
http://dx.doi.org/10.3389/fpsyg.2022.874230
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author Morris, Bradley J.
Todaro, Rachael
Arner, Tracy
Roche, Jennifer M.
author_facet Morris, Bradley J.
Todaro, Rachael
Arner, Tracy
Roche, Jennifer M.
author_sort Morris, Bradley J.
collection PubMed
description Predictions begin with an extrapolation of the properties of their underlying representations to forecast a future state not presently in evidence. For numerical predictions, sets of numbers are summarized and the result forms the basis of and constrains numerical predictions. One open question is how the accuracy of underlying representations influences predictions, particularly numerical predictions. It is possible that inaccuracies in individual number representations are randomly distributed and averaged over during summarization (e.g., wisdom of crowds). It is also possible that inaccuracies are not random and lead to errors in predictions. We investigated this question by measuring the accuracy of individual number representations of 279 children ages 8–12 years, using a 0–1,000 number line, and numerical predictions, measured using a home run derby task. Consistent with prior research, our results from mixed random effects models evaluating percent absolute error (PAE; prediction error) demonstrated that third graders’ representations of individual numbers were less accurate, characterized by overestimation errors, and were associated with overpredictions (i.e., predictions above the set mean). Older children had more accurate individual number representations and a slight tendency to underpredict (i.e., predictions below the set mean). The results suggest that large, systematic inaccuracies appear to skew predictions while small, random errors appear to be averaged over during summarization. These findings add to our understanding of summarization and its role in numerical predictions.
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spelling pubmed-92418302022-06-30 How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions? Morris, Bradley J. Todaro, Rachael Arner, Tracy Roche, Jennifer M. Front Psychol Psychology Predictions begin with an extrapolation of the properties of their underlying representations to forecast a future state not presently in evidence. For numerical predictions, sets of numbers are summarized and the result forms the basis of and constrains numerical predictions. One open question is how the accuracy of underlying representations influences predictions, particularly numerical predictions. It is possible that inaccuracies in individual number representations are randomly distributed and averaged over during summarization (e.g., wisdom of crowds). It is also possible that inaccuracies are not random and lead to errors in predictions. We investigated this question by measuring the accuracy of individual number representations of 279 children ages 8–12 years, using a 0–1,000 number line, and numerical predictions, measured using a home run derby task. Consistent with prior research, our results from mixed random effects models evaluating percent absolute error (PAE; prediction error) demonstrated that third graders’ representations of individual numbers were less accurate, characterized by overestimation errors, and were associated with overpredictions (i.e., predictions above the set mean). Older children had more accurate individual number representations and a slight tendency to underpredict (i.e., predictions below the set mean). The results suggest that large, systematic inaccuracies appear to skew predictions while small, random errors appear to be averaged over during summarization. These findings add to our understanding of summarization and its role in numerical predictions. Frontiers Media S.A. 2022-06-15 /pmc/articles/PMC9241830/ /pubmed/35783810 http://dx.doi.org/10.3389/fpsyg.2022.874230 Text en Copyright © 2022 Morris, Todaro, Arner and Roche. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Morris, Bradley J.
Todaro, Rachael
Arner, Tracy
Roche, Jennifer M.
How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title_full How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title_fullStr How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title_full_unstemmed How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title_short How Does the Accuracy of Children’s Number Representations Influence the Accuracy of Their Numerical Predictions?
title_sort how does the accuracy of children’s number representations influence the accuracy of their numerical predictions?
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241830/
https://www.ncbi.nlm.nih.gov/pubmed/35783810
http://dx.doi.org/10.3389/fpsyg.2022.874230
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