Lonnemann Jan, Li Su, Zhao Pei, Li Peng, Linkersdörfer Janosch, Lindberg Sven, Hasselhorn Marcus, Yan Song
Department of Education and Human Development, German Institute for International Educational Research (DIPF), Frankfurt am Main, Germany.
Center for Individual Development and Adaptive Education of Children at Risk, Frankfurt am Main, Germany.
PLoS One. 2017 Apr 6;12(4):e0174991. doi: 10.1371/journal.pone.0174991. eCollection 2017.
Human beings are assumed to possess an approximate number system (ANS) dedicated to extracting and representing approximate numerical magnitude information. The ANS is assumed to be fundamental to arithmetic learning and has been shown to be associated with arithmetic performance. It is, however, still a matter of debate whether better arithmetic skills are reflected in the ANS. To address this issue, Chinese and German adults were compared regarding their performance in simple arithmetic tasks and in a non-symbolic numerical magnitude comparison task. Chinese participants showed a better performance in solving simple arithmetic tasks and faster reaction times in the non-symbolic numerical magnitude comparison task without making more errors than their German peers. These differences in performance could not be ascribed to differences in general cognitive abilities. Better arithmetic skills were thus found to be accompanied by a higher speed of retrieving non-symbolic numerical magnitude knowledge but not by a higher precision of non-symbolic numerical magnitude representations. The group difference in the speed of retrieving non-symbolic numerical magnitude knowledge was fully mediated by the performance in arithmetic tasks, suggesting that arithmetic skills shape non-symbolic numerical magnitude processing skills.
人们假定人类拥有一个专门用于提取和表征近似数值大小信息的近似数字系统（ANS）。ANS被认为是算术学习的基础，并且已被证明与算术表现相关。然而，更好的算术技能是否反映在ANS中仍是一个有争议的问题。为了解决这个问题，对中国和德国成年人在简单算术任务和非符号数值大小比较任务中的表现进行了比较。中国参与者在解决简单算术任务方面表现更好，在非符号数值大小比较任务中的反应时间更快，且比德国同龄人犯的错误更少。这些表现上的差异不能归因于一般认知能力的差异。因此，发现更好的算术技能伴随着更高的提取非符号数值大小知识的速度，而不是更高的非符号数值大小表征精度。提取非符号数值大小知识速度的组间差异完全由算术任务中的表现所介导，这表明算术技能塑造了非符号数值大小处理技能。
