Department of Cognitive Sciences, University of California, Irvine, CA 92697-5100, USA.
Cognition. 2011 Sep;120(3):391-402. doi: 10.1016/j.cognition.2010.10.003. Epub 2010 Nov 24.
Lee and Sarnecka (2010) 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.
李和萨内卡（2010）开发了一种贝叶斯模型，用于研究儿童在数量知识测试中的行为。本文提出了该模型的两个新扩展，并将模型应用于新数据。在第一个扩展中，该模型用于评估关于儿童行为背后的概念知识的竞争理论。一个理论是“知识水平”理论，基本上是一个涉及真正概念变化的“阶段”理论。另一个理论是“近似意义”理论，它假设儿童的概念知识相对稳定，尽管随着时间的推移表现会有所提高。在第二个扩展中，该模型用于询问同一个潜在的心理变量（儿童的数字知识水平）是否可以同时解释两个具有不同性能要求的任务（Give-N 任务和 Fast-Cards 任务）上的行为。这两个演示共同展示了贝叶斯建模方法在提高我们对人类认知发展的理解方面的潜力。
