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Non-Bayesian noun generalization in 3- to 5-year-old children: Probing the role of prior knowledge in the suspicious coincidence effect

机译:3至5岁儿童的非贝叶斯名词概括:探究先验知识在可疑巧合效应中的作用

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摘要

It is unclear how children learn labels for multiple overlapping categories such as “Labrador,” “dog,” and “animal.” suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and adults. Here, we report data testing a developmental prediction of the Bayesian model—that more knowledge should lead to narrower category inferences when presented with multiple subordinate examples. Two experiments did not support this prediction. Children with more category knowledge showed broader generalization when presented with multiple subordinate examples, compared to less knowledgeable children and adults. This implies a U-shaped developmental trend. The Bayesian model was not able to account for these data, even with inputs that reflected the similarity judgments of children. We discuss implications for the Bayesian model including a combined Bayesian/morphological knowledge account that could explain the demonstrated U-shaped trend.
机译:尚不清楚儿童如何学习多个重叠类别的标签,例如“拉布拉多”,“狗”和“动物”。建议学习者借助贝叶斯推理来推断正确的意思。他们在贝叶斯模型中实例化了这些声明,并与学龄前儿童和成人进行了测试。在这里,我们报告的数据是对贝叶斯模型的发展预测进行测试的数据,即当出现多个下属示例时,更多的知识应导致较窄的类别推断。有两个实验不支持此预测。与知识较少的儿童和成人相比,拥有更多类别知识的儿童在通过多个下属示例展示时表现出更广泛的概括。这意味着U形发展趋势。即使使用反映儿童相似性判断的输入,贝叶斯模型也无法解释这些数据。我们讨论了贝叶斯模型的含义,其中包括可以解释已证明的U形趋势的贝叶斯/形态学知识组合。

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