Mechanisms Underlying Numerical and Mathematical Cognition

随着世界经济越来越依赖科技创新，了解影响科学、技术、工程和数学(STEM)领域成功的因素变得越来越重要。熟练的空间处理和数值/数学处理是STEM的重要组成部分，在空间任务上表现得越好的人也具有更高的数学能力(例如，鲁宾斯基S数字线越多，他们的数学能力往往越高)(Holloway Siegler&Ramani，2009)。这项拟议的研究检验了这一新的观点，即这种映射过程至少部分地解释了所观察到的空间加工和数值加工之间的关系，认为空间资源参与了心理数字线的创建(例如，Gunderson，Ramirez，Beilock，&Levine，2012)。这项提议中的研究旨在考察空间处理在需要和不需要比较数值大小的数值和数学任务中的作用，检验空间处理涉及生成结构映射到其上的线性表示的假设，并检查各种类型的空间能力的个体差异如何与需要和不需要比较数值大小的数值和数学任务的表现有关。这项工作不仅有可能深入了解数字和数学认知背后的基本认知机制，而且还有可能为旨在提高数学成绩和增加有资格进入STEM职业并取得成功的候选人数量的基于空间处理的干预措施提供信息。

As world economies are becoming increasingly more reliant on scientific and technological innovation, understanding the factors that influence success in science, technology, engineering, and mathematics (STEM) fields is becoming increasingly more important. Proficiency in spatial processing and numerical/mathematical processing are important components of STEM and people who perform better on spatial tasks also have higher mathematical ability (e.g., Lubinski s number lines are, the higher their mathematical ability tends to be (Holloway Siegler & Ramani, 2009). The proposed research examines the novel idea that this mapping process is, at least partially, responsible for the observed relation between spatial processing and numerical processing, arguing that spatial resources are engaged in the creation of the mental number line (e.g., Gunderson, Ramirez, Beilock, & Levine, 2012). The research within this proposal serves to examine the role of spatial processing in numerical and mathematical tasks that do and do not require comparisons of numerical magnitude, test the hypothesis that spatial processing is involved in the generation of a linear representation onto which constructs are mapped and examine how individual differences in various types of spatial abilities relate to performance on numerical and mathematical tasks that do and do not require the comparisons of numerical magnitude. This work has the potential to not only garner insights into the basic cognitive mechanisms underlying numerical and mathematical cognition, but also to inform spatial-processing-based interventions aimed at improving achievement in mathematics and increasing the number of candidates qualified to enter and succeed in STEM careers.