Number-knower levels in young children: insights from Bayesian modeling.

Number-knower levels in young children: insights from Bayesian modeling.
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DOI:
10.1016/j.cognition.2010.10.003
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发表时间:
2011-09
期刊:
影响因子:
3.4
通讯作者:
Sarnecka BW
Sarnecka BW
中科院分区:
心理学2区
文献类型:
--
作者:
Lee MD;Sarnecka BW

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开发了一个贝叶斯模型的幼儿的行为的给N测试的数字知识。本文提出了两个新的扩展模型,并将该模型应用到新的数据。在第一个扩展中,该模型被用来评估有关儿童行为的概念知识的竞争理论。一种是知识层次理论,它基本上是一种涉及真实的概念变化的“阶段”理论。另一种是近似意义理论,它假设儿童的概念知识是相对恒定的,尽管表现会随着时间的推移而提高。在第二个扩展中,该模型被用来询问是否相同的潜在心理变量(儿童的数字知识水平)可以同时占行为的两个任务(给N任务和快速卡任务)具有不同的性能要求。总之,这两个演示显示了贝叶斯建模方法的潜力,以提高我们对人类认知发展的理解。
developed a Bayesian model of young children’s behavior on the Give-N test of number knowledge. This paper presents two new extensions of the model, and applies the model to new data. In the first extension, the model is used to evaluate competing theories about the conceptual knowledge underlying children’s behavior. One, the knower-levels theory, is basically a “stage” theory involving real conceptual change. The other, the approximate-meanings theory, assumes that the child’s conceptual knowledge is relatively constant, although performance improves over time. In the second extension, the model is used to ask whether the same latent psychological variable (a child’s number-knower-level) can simultaneously account for behavior on two tasks (the Give-N task and the Fast-Cards task) with different performance demands. Together, these two demonstrations show the potential of the Bayesian modeling approach to improve our understanding of the development of human cognition.
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