Department of Psychology, University of Pittsburgh, Pittsburgh 15260, PA, USA; Learning Research and Development Center, University of Pittsburgh, Pittsburgh 15260, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh 15260, PA, USA.
Department of Psychology, University of Pittsburgh, Pittsburgh 15260, PA, USA; Learning Research and Development Center, University of Pittsburgh, Pittsburgh 15260, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh 15260, PA, USA.
Cognition. 2022 Jul;224:105067. doi: 10.1016/j.cognition.2022.105067. Epub 2022 Feb 24.
Most adults have access to two different number systems to represent numerical information: an exact number system, which relies on different forms of number symbols to represent exact numerical information, and an approximate number system, which allows for approximate estimates of numerical quantities. Here we investigate the integration between the symbolic and non-symbolic numerical information (i.e., "numerical integration"), and how numerical integration relates to adults' formal math abilities. We administered two tasks to measure numerical integration. For a number comparison task with non-symbolic dot arrays and Arabic numerals, participants indicated the larger of two sequentially presented stimuli that were same-format (dot-dot or numeral-numeral), or mixed-format (dot-numeral or numeral-dot). For a number-letter discrimination task, participants identified Arabic numerals or letter pairs that co-occurred with dot arrays (matching or mismatching the quantity represented by the numeral). In the number comparison task, participants were significantly slower when comparing mixed-format stimuli, especially when Arabic numerals were presented first and dot arrays second, suggesting estrangement between symbolic and non-symbolic numerical information and an asymmetry depending on the order in which the numerical information is presented. In contrast, in the number-letter discrimination task, participants were significantly faster in number-letter discrimination for matching dot arrays and numerals, suggesting integration between symbolic and non-symbolic numerical information. Surprisingly, some measures of numerical estrangement derived from the number comparison task significantly correlated with adults' performance on a standardized math assessment. Thus, we conclude that numerical integration or estrangement is task-dependent, and adults with greater levels of symbolic estrangement tend to have higher math skills.
一种是精确数字系统，它依赖于不同形式的数字符号来表示精确的数值信息；另一种是近似数字系统，它允许对数值量进行近似估计。在这里，我们研究了符号和非符号数值信息之间的整合（即“数值整合”），以及数值整合如何与成年人的正式数学能力相关。我们进行了两项任务来测量数值整合。对于一个带有非符号点数组和阿拉伯数字的数字比较任务，参与者需要指出两个连续呈现的刺激中较大的一个，这两个刺激的呈现形式相同（点-点或数字-数字），或者混合形式（点-数字或数字-点）。对于数字-字母辨别任务，参与者需要识别与点数组一起出现的阿拉伯数字或字母对（与数字表示的数量匹配或不匹配）。在数字比较任务中，当比较混合形式的刺激时，参与者的反应明显较慢，尤其是当首先呈现阿拉伯数字，然后呈现点数组时，这表明符号和非符号数值信息之间存在疏远，并且这种疏远取决于数值信息呈现的顺序。相比之下，在数字-字母辨别任务中，参与者在匹配的点数组和数字的数字-字母辨别中反应明显更快，这表明符号和非符号数值信息之间存在整合。令人惊讶的是，一些从数字比较任务中得出的数值疏远的度量指标与成年人在标准化数学评估中的表现显著相关。因此，我们得出结论，数值整合或疏远是任务依赖的，具有较高符号疏远程度的成年人往往具有更高的数学技能。
