Quantifying stimulus, response, and numerical biases

描述（由申请人提供）：尽管人们无法对比例做出直观判断（综述见Rothman & Kiviniemi，1999）已被证明会导致对健康相关问题的判断不佳（Kaplan，哈梅尔，& Schimmel，1985），但相对较少的研究旨在理解比例的认知表征。目前的建议将填补这一空白，（1）提供广泛的数据的内部表示的比例，（2）生成模型的认知表示的比例类似的模型存在的认知表示的整数。目前的建议还涉及经验在形成和维持数字偏差方面的作用。了解这些符号是如何以及为什么被误解的，将导致减少这些偏见的技术，这反过来又将导致更有效的数学教学方法。所提出的方法结合了实证研究，数值统计程序，探索性分析和计算建模。特别是，拟议的研究将评估的距离效应的三个数字格式和三个刺激，其中数量是固有的，评估与跨通道匹配的六个刺激的偏差，并使用数值统计模型来估计参数的数值偏差。一旦识别和描述了数字偏差的功能形式，我将研究经验在这些偏差的形成和维持中的作用。

DESCRIPTION (provided by applicant): Although people's inability to make intuitive judgments about proportions (for a review, see Rothman & Kiviniemi, 1999) has been shown to lead to poor judgments about health related issues (Kaplan, Hammel, & Schimmel, 1985), relatively little research has been directed at understanding the cognitive representation of proportions. The current proposal will fill this gap by (1) providing extensive data on the internal representation of proportions, and (2) generating models of the cognitive representation of proportions similar to the models that exist for the cognitive representation of integers. The current proposal also addresses the role of experience in the formation and maintenance of numerical biases. Learning how and why these symbols are misinterpreted will lead to techniques to reduce these biases, which in turn will lead to more effective methods of teaching mathematics. The proposed approach combines empirical research, numerical statistical procedures, exploratory analysis, and computational modeling. In particular, the proposed research will assess the distance effect for three numerical formats and three stimuli in which quantity is inherent, assess the biases associated with cross-modality matching for the six stimuli, and use numerical statistical models to estimate the parameters of the numerical biases. Once the functional form of numerical biases are identified and described, I will study the role of experience in the formation and maintenance of these biases.