Children can solve Bayesian problems: the role of representation in mental computation
Zhu, LQ; Gigerenzer, G; G. Gigerenzer
摘要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.; 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.
关键词Bayesian problems computation binary hypothesis
学科领域认知心理学 ; 发展心理学
2006
语种英语
发表期刊COGNITION
ISSN0010-0277
卷号98期号:3页码:287-308
期刊论文类型Article
收录类别SSCI
WOS记录号WOS:000234940800005
引用统计
被引频次:99[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/5243
专题中国科学院心理研究所回溯数据库(1956-2010)
通讯作者G. Gigerenzer
作者单位1.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
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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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