Number-knower levels in young children: insights from Bayesian modeling
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Updated: Jun 6, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Michael D Lee1, Barbara W Sarnecka
1Department of Cognitive Sciences, University of California, Irvine, CA 92697-5100, USA. mdlee@uci.edu
Abstract:
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.
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