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Children can solve Bayesian problems: the role of representation in mental computation
Zhu, LQ; Gigerenzer, G; G. Gigerenzer
2006
Source PublicationCOGNITION
ISSN0010-0277
SubtypeArticle
Volume98Issue:3Pages:287-308
AbstractCan children reason the Bayesian way? We argue that the answer to this question depends on how numbers are represented, because a representation can do part of the computation. We test, for the first time, whether Bayesian reasoning can be elicited in children by means of natural frequencies. We show that when information was presented to fourth, fifth, and sixth graders in terms of probabilities, their ability to estimate the Bayesian posterior probability was zero. Yet when the same information was presented in natural frequencies, Bayesian reasoning showed a steady increase from fourth to sixth grade, reaching an average level of 19, 39, and 53%, respectively, in two studies. Sixth graders' performance with natural frequencies matched the performance of adults with probabilities. But this general increase was accompanied by striking individual differences. More than half of the sixth graders solved most or all problems, whereas one third could not solve a single one. An analysis of the children's responses provides evidence for the use of three non-Bayesian strategies. These follow an overlapping wave model of development and continue to be observed in the minds of adults. More so than adults' probabilistic reasoning, children's reasoning depends on a proper representation of information.; Can children reason the Bayesian way? We argue that the answer to this question depends on how numbers are represented, because a representation can do part of the computation. We test, for the first time, whether Bayesian reasoning can be elicited in children by means of natural frequencies. We show that when information was presented to fourth, fifth, and sixth graders in terms of probabilities, their ability to estimate the Bayesian posterior probability was zero. Yet when the same information was presented in natural frequencies, Bayesian reasoning showed a steady increase from fourth to sixth grade, reaching an average level of 19, 39, and 53%, respectively, in two studies. Sixth graders' performance with natural frequencies matched the performance of adults with probabilities. But this general increase was accompanied by striking individual differences. More than half of the sixth graders solved most or all problems, whereas one third could not solve a single one. An analysis of the children's responses provides evidence for the use of three non-Bayesian strategies. These follow an overlapping wave model of development and continue to be observed in the minds of adults. More so than adults' probabilistic reasoning, children's reasoning depends on a proper representation of information. (c) 2005 Elsevier B.V. All rights reserved.
KeywordBayesian problems computation binary hypothesis
Subject Area认知心理学 ; 发展心理学
Indexed BySSCI
Language英语
WOS IDWOS:000234940800005
Citation statistics
Cited Times:67[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/5243
Collection中国科学院心理研究所回溯数据库(1956-2010)
Corresponding AuthorG. Gigerenzer
Affiliation1.Max Planck Inst Human Dev, Ctr Adapt Behav & Cognit, D-14195 Berlin, Germany
2.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Beijing 100864, Peoples R China
Recommended Citation
GB/T 7714
Zhu, LQ,Gigerenzer, G,G. Gigerenzer. Children can solve Bayesian problems: the role of representation in mental computation[J]. COGNITION,2006,98(3):287-308.
APA Zhu, LQ,Gigerenzer, G,&G. Gigerenzer.(2006).Children can solve Bayesian problems: the role of representation in mental computation.COGNITION,98(3),287-308.
MLA Zhu, LQ,et al."Children can solve Bayesian problems: the role of representation in mental computation".COGNITION 98.3(2006):287-308.
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