Cognitive Processes Underlying Ratio Representation Across Development

整个发展过程中比率表示的认知过程

• 批准号: 10191818
• 负责人: Michelle Hurst
• 金额: $ 8.99万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10191818
• 关键词: Academic achievement; Address; Adult; Behavior; Behavioral; Chicago; Child; Cognition; Cognitive; Computer Models; Data; Decision Making; Development; Dimensions; Discrimination; Goals; Hand; Infant; Investigation; Juice; Knowledge; Lead; Medical; Mentors; Methodology; Methods; Modeling; Participant; Pattern; Performance; Phase; Positioning Attribute; Process; Psychology; Reporting; Risk; Specific qualifier value; Stimulus; Structure; Testing; Time; Training; Universities; Water; Work; base; cognitive development; cognitive process; evidence base; infancy; insight; mathematical model; novel; prevent; recruit; skills; theories

PROJECT SUMMARY/ABSTRACT Proportional reasoning is a critical skill, both for every day decision making, such as evaluating financial and medical risk, and for academic achievement. Prior work reveals that proportional reasoning varies across two critical dimensions: (1) the type of quantity on which the proportion is based and (2) development. In particular, children and adults are worse at proportional reasoning when the proportion is based on discrete number (e.g., the proportion of M&Ms that are red) versus continuous amount (e.g., proportion of juice that is just water). Furthermore, error-prone performance with discrete proportion in particular may vary developmentally, with infants and young children being less error-prone than older children and adults. However, little is known about the shared cognitive mechanisms that underly proportional reasoning and how these mechanisms may vary across contexts and development. The current proposal aims to address this critical gap. The proposed project will identify which cognitive mechanisms are independent of the specific type of quantitative context, and thus underly proportional reasoning more generally, and which mechanisms are unique to the specific type of quantity at hand. Using a developmental and computational approach, the Specific Aims target three distinct possible mechanisms that may differ across discrete and continuous proportion: cognitive representations (Aim 1), cognitive processes (Aim 2), and symbolic strategies (Aim 2). This approach will provide novel theoretical insight into the cognitive mechanisms that underly proportional reasoning across contexts and development, as well as how these mechanisms can be leveraged to support proportional reasoning more generally (Aim 3). During the K-Phase of the project, the candidate will characterize the precision with which infants, children, and adults represent proportional information, and how it differs in discrete and continuous contexts (Aim 1). Using a computational modeling approach, Aim 2 will test formal mathematical models of cognitive processes that could explain the behavioral patterns found in Aim 1. During the R-Phase, Aim 2 will also test the often-reported but largely untested hypothesis that people use symbolic number strategies with discrete, but not continuous, proportion. Lastly, Aim 3 will leverage insights about specific cognitive mechanisms gained in the prior aims to test novel predictions about how to support both young children’s proportional reasoning and probabilistic decision making in adults (Study 5). A long-term goal of the candidate is to develop a Theory of Proportion that explains behavior across a range of contexts and across development. The mentored phase will take place in the University of Chicago’s Psychology Department and the proposed training in theory-building, infant methods (Aim 1), and computational modeling approaches (Aim 2) will put the candidate in an excellent position to become a methodological and theoretical leader in the field of cognitive development.

项目摘要/摘要 比例推理都是至关重要的技能，无论是每天的决策，例如评估财务和 医疗风险，以及为了学业成就。先前的工作表明，比例推理在两个方面有所不同 临界维度：（1）比例所基于的数量和（2）开发的数量类型。尤其， 当比例基于离散数时，儿童和成人在比例推理时会更糟（例如， 红色的M＆M的比例与连续数量（例如，仅是水的果汁的比例）。 此外，特别是易于出错的性能，特别是离散比例的性能可能会有所不同，并且 婴儿和幼儿比大儿童和成人少犯错。但是，对 基本推理以及这些机制如何变化的共同认知机制 跨环境和发展。当前的提案旨在解决这一关键差距。拟议的项目 将确定哪些认知机制独立于定量背景的特定类型，因此 基础推理的基本推理更一般，哪些机制是特定类型的特定类型 手头的数量。使用发展和计算方法，特定目的针对三个不同的目标 在离散和连续比例之间可能有所不同的可能机制：认知表示（目标） 1），认知过程（AIM 2）和符号策略（AIM 2）。这种方法将提供新颖的理论 深入了解跨环境和发展的基本推理的认知机制， 以及如何利用这些机制来更普遍地支持比例推理（AIM 3）。 在该项目的K阶段期间，候选人将表征婴儿，儿童和 成年人代表比例信息，以及在离散和连续环境中的不同之处（AIM 1）。使用 AIM 2是一种计算建模方法，将测试认知过程的形式数学模型 可以解释AIM 1中发现的行为模式。在R期间，AIM 2还将测试经常报告的 但是在很大程度上未经测试的假设是，人们使用具有离散但不连续的符号数字策略， 部分。最后，AIM 3将利用有关先前目标获得的特定认知机制的见解 测试有关如何支持两个幼儿比例推理和概率的新颖预测 成人决策（研究5）。 候选人的长期目标是发展一个比例理论，该理论解释了一系列范围的行为 环境和整个发展。修改阶段将在芝加哥大学的心理学 部门和理论建设，婴儿方法（AIM 1）和计算建模的拟议培训 方法（AIM 2）将使候选人处于良好的位置，成为一种方法论和理论 认知发展领域的领导者。