Barnard College, Columbia University, New York, NY 10027, United States.
Cognition. 2010 Aug;116(2):204-16. doi: 10.1016/j.cognition.2010.05.003. Epub 2010 May 26.
A dedicated, non-symbolic, system yielding imprecise representations of large quantities (approximate number system, or ANS) has been shown to support arithmetic calculations of addition and subtraction. In the present study, 5-7-year-old children without formal schooling in multiplication and division were given a task requiring a scalar transformation of large approximate numerosities, presented as arrays of objects. In different conditions, the required calculation was doubling, quadrupling, or increasing by a fractional factor (2.5). In all conditions, participants were able to represent the outcome of the transformation at above-chance levels, even on the earliest training trials. Their performance could not be explained by processes of repeated addition, and it showed the critical ratio signature of the ANS. These findings provide evidence for an untrained, intuitive process of calculating multiplicative numerical relationships, providing a further foundation for formal arithmetic instruction.
已经证明,一种专注的、非符号的、能够产生大量不精确表示的系统(近似数量系统,或 ANS)支持加法和减法的算术计算。在本研究中,没有接受过乘法和除法正规教育的 5-7 岁儿童被给予一项需要对大近似数量进行标量变换的任务,这些数量以物体数组的形式呈现。在不同的条件下,所需的计算是翻倍、四倍或增加分数因子(2.5)。在所有条件下,参与者都能够以上限概率水平表示变换的结果,甚至在最早的训练试验中也是如此。他们的表现不能用重复加法的过程来解释,而是表现出了 ANS 的关键比率特征。这些发现为未经训练的、直觉的乘法数值关系计算过程提供了证据,为正式的算术教学提供了进一步的基础。