Indiana University, Department of Psychological and Brain Sciences, 1101 E Tenth St., Bloomington, IN 47405-7007, United States.
Cognition. 2013 Feb;126(2):258-67. doi: 10.1016/j.cognition.2012.10.007. Epub 2012 Nov 17.
Much research has demonstrated a shape bias in categorizing and naming solid objects. This research has shown that when an entity is conceptualized as an individual object, adults and children attend to the object's shape. Separate research in the domain of numerical cognition suggest that there are distinct processes for quantifying small and large sets of discrete items. This research shows that small set discrimination, comparison, and apprehension is often precise for 1-3 and sometimes 4 items; however, large numerosity representation is imprecise. Results from three experiments suggest a link between the processes for small and large number representation and the shape bias in a forced choice categorization task using naming and non-naming procedures. Experiment 1 showed that adults generalized a newly learned name for an object to new instances of the same shape only when those instances were presented in sets of less than 3 or 4. Experiment 2 showed that preschool children who were monolingual speakers of three different languages were also influenced by set size when categorizing objects in sets. Experiment 3 extended these results and showed the same effect in a non-naming task and when the novel noun was presented in a count-noun syntax frame. The results are discussed in terms of a relation between the precision of object representation and the precision of small and large number representation.
许多研究表明,在对实体进行分类和命名时存在形状偏见。这些研究表明,当一个实体被概念化为一个单独的物体时,成年人和儿童会关注物体的形状。在数值认知领域的独立研究表明,对小数量和大数量离散项目进行量化有不同的过程。这些研究表明,小数量的区分、比较和理解通常对 1-3 个项目非常准确,有时甚至对 4 个项目也很准确;然而,对大量数量的表示则不够准确。三项实验的结果表明,小数量和大数量表示的过程与在使用命名和非命名程序的强制选择分类任务中的形状偏见之间存在联系。实验 1 表明,只有当新实例的数量少于 3 或 4 个时,成年人才能将新学习的物体名称推广到同一形状的新实例上。实验 2 表明,来自三种不同语言的单语讲者的学前儿童在分类物体时也会受到集合大小的影响。实验 3 扩展了这些结果,并在非命名任务中以及在计数名词句法框架中呈现新名词时显示了相同的效果。这些结果是根据物体表示的精度与小数量和大数量表示的精度之间的关系来讨论的。