Faster learners transfer their knowledge better: Behavioral, mnemonic, and neural mechanisms of individual differences in children's learning.

Brain circuits Individual differences Learning Near transfer Neural representations Tutoring

Journal

Developmental cognitive neuroscience
ISSN: 1878-9307
Titre abrégé: Dev Cogn Neurosci
Pays: Netherlands
ID NLM: 101541838

Informations de publication

Date de publication:
12 2019
Historique:
received: 01 06 2019
revised: 03 10 2019
accepted: 12 10 2019
pubmed: 12 11 2019
medline: 13 3 2020
entrez: 12 11 2019
Statut: ppublish

Résumé

Why some children learn, and transfer their knowledge to novel problems, better than others remains an important unresolved question in the science of learning. Here we developed an innovative tutoring program and data analysis approach to investigate individual differences in neurocognitive mechanisms that support math learning and "near" transfer to novel, but structurally related, problems in elementary school children. Following just five days of training, children performed recently trained math problems more efficiently, with greater use of memory-retrieval-based strategies. Crucially, children who learned faster during training performed better not only on trained problems but also on novel problems, and better discriminated trained and novel problems in a subsequent recognition memory task. Faster learners exhibited increased similarity of neural representations between trained and novel problems, and greater differentiation of functional brain circuits engaged by trained and novel problems. These results suggest that learning and near transfer are characterized by parallel learning-rate dependent local integration and large-scale segregation of functional brain circuits. Our findings demonstrate that speed of learning and near transfer are interrelated and identify the neural mechanisms by which faster learners transfer their knowledge better. Our study provides new insights into the behavioral, mnemonic, and neural mechanisms underlying children's learning.

Identifiants

pubmed: 31710975
pii: S1878-9293(19)30306-8
doi: 10.1016/j.dcn.2019.100719
pmc: PMC6974913
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

100719

Subventions

Organisme : NIMH NIH HHS
ID : K01 MH101394
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH084164
Pays : United States
Organisme : NIMH NIH HHS
ID : K99 MH105601
Pays : United States
Organisme : NICHD NIH HHS
ID : R37 HD094623
Pays : United States
Organisme : NICHD NIH HHS
ID : R01 HD059205
Pays : United States

Informations de copyright

Copyright © 2019. Published by Elsevier Ltd.

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Auteurs

Hyesang Chang (H)

Department of Psychiatry & Behavioral Sciences, Stanford, CA 94305, United States. Electronic address: changh@stanford.edu.

Miriam Rosenberg-Lee (M)

Department of Psychiatry & Behavioral Sciences, Stanford, CA 94305, United States; Department of Psychology, Rutgers University, Newark, NJ 07102, United States.

Shaozheng Qin (S)

Department of Psychiatry & Behavioral Sciences, Stanford, CA 94305, United States; State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Faculty of Psychology at Beijing Normal University, Beijing, China.

Vinod Menon (V)

Department of Psychiatry & Behavioral Sciences, Stanford, CA 94305, United States; Department of Neurology & Neurological Sciences, Stanford, CA 94305, United States; Stanford Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, United States. Electronic address: menon@stanford.edu.

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