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Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change

Children’s cognitive control and knowledge at school entry predict growth rates in analogical reasoning skill over time; however, the mechanisms by which these factors interact and impact learning are unclear. We propose that inhibitory control (IC) is critical for developing both the relational rep...

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Autores principales: Doumas, Leonidas A. A., Morrison, Robert G., Richland, Lindsey E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095010/
https://www.ncbi.nlm.nih.gov/pubmed/30140242
http://dx.doi.org/10.3389/fpsyg.2018.01235
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author Doumas, Leonidas A. A.
Morrison, Robert G.
Richland, Lindsey E.
author_facet Doumas, Leonidas A. A.
Morrison, Robert G.
Richland, Lindsey E.
author_sort Doumas, Leonidas A. A.
collection PubMed
description Children’s cognitive control and knowledge at school entry predict growth rates in analogical reasoning skill over time; however, the mechanisms by which these factors interact and impact learning are unclear. We propose that inhibitory control (IC) is critical for developing both the relational representations necessary to reason and the ability to use these representations in complex problem solving. We evaluate this hypothesis using computational simulations in a model of analogical thinking, Discovery of Relations by Analogy/Learning and Inference with Schemas and Analogy (DORA/LISA; Doumas et al., 2008). Longitudinal data from children who solved geometric analogy problems repeatedly over 6 months show three distinct learning trajectories though all gained somewhat: analogical reasoners throughout, non-analogical reasoners throughout, and transitional – those who start non-analogical and grew to be analogical. Varying the base level of top-down lateral inhibition in DORA affected the model’s ability to learn relational representations, which, in conjunction with inhibition levels used in LISA during reasoning, simulated accuracy rates and error types seen in the three different learning trajectories. These simulations suggest that IC may not only impact reasoning ability but may also shape the ability to acquire relational knowledge given reasoning opportunities.
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spelling pubmed-60950102018-08-23 Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change Doumas, Leonidas A. A. Morrison, Robert G. Richland, Lindsey E. Front Psychol Psychology Children’s cognitive control and knowledge at school entry predict growth rates in analogical reasoning skill over time; however, the mechanisms by which these factors interact and impact learning are unclear. We propose that inhibitory control (IC) is critical for developing both the relational representations necessary to reason and the ability to use these representations in complex problem solving. We evaluate this hypothesis using computational simulations in a model of analogical thinking, Discovery of Relations by Analogy/Learning and Inference with Schemas and Analogy (DORA/LISA; Doumas et al., 2008). Longitudinal data from children who solved geometric analogy problems repeatedly over 6 months show three distinct learning trajectories though all gained somewhat: analogical reasoners throughout, non-analogical reasoners throughout, and transitional – those who start non-analogical and grew to be analogical. Varying the base level of top-down lateral inhibition in DORA affected the model’s ability to learn relational representations, which, in conjunction with inhibition levels used in LISA during reasoning, simulated accuracy rates and error types seen in the three different learning trajectories. These simulations suggest that IC may not only impact reasoning ability but may also shape the ability to acquire relational knowledge given reasoning opportunities. Frontiers Media S.A. 2018-07-24 /pmc/articles/PMC6095010/ /pubmed/30140242 http://dx.doi.org/10.3389/fpsyg.2018.01235 Text en Copyright © 2018 Doumas, Morrison and Richland. http://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
Doumas, Leonidas A. A.
Morrison, Robert G.
Richland, Lindsey E.
Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title_full Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title_fullStr Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title_full_unstemmed Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title_short Individual Differences in Relational Learning and Analogical Reasoning: A Computational Model of Longitudinal Change
title_sort individual differences in relational learning and analogical reasoning: a computational model of longitudinal change
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095010/
https://www.ncbi.nlm.nih.gov/pubmed/30140242
http://dx.doi.org/10.3389/fpsyg.2018.01235
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