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: 10460325
• 负责人: Michelle Hurst
• 金额: $ 8.78万
• 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/10460325
• 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; Persons; 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.

项目概要/摘要 比例推理对于日常决策（例如评估财务和决策）来说是一项关键技能。 医疗风险和学业成就。先前的工作表明，比例推理在两种情况下有所不同 关键维度：(1) 比例所依据的数量类型；(2) 发展。尤其， 当比例基于离散数字时（例如， 红色 M&M 巧克力豆的比例）与连续量（例如纯水果汁的比例）。 此外，特别是离散比例的容易出错的性能可能会随着发展而变化， 婴儿和幼儿比年龄较大的儿童和成人更不容易出错。然而，人们对此知之甚少 比例推理背后的共同认知机制以及这些机制如何变化 跨环境和发展。当前的提案旨在解决这一关键差距。拟议项目 将确定哪些认知机制独立于特定类型的定量背景，从而 更一般地说，比例推理不足，以及哪些机制是特定类型所独有的 手头的数量。使用开发和计算方法，具体目标针对三个不同的目标 离散和连续比例可能不同的可能机制：认知表征（目标 1）、认知过程（目标 2）和符号策略（目标 2）。该方法将提供新颖的理论 洞察跨情境和发展的比例推理的认知机制，如 以及如何利用这些机制来支持更普遍的比例推理（目标 3）。 在项目的 K 阶段，候选人将描述婴儿、儿童和儿童的精确度。 成年人代表比例信息，以及它在离散和连续环境中的差异（目标 1）。使用 作为一种计算建模方法，目标 2 将测试认知过程的正式数学模型 可以解释目标 1 中发现的行为模式。在 R 阶段，目标 2 还将测试经常报告的行为模式 但很大程度上未经检验的假设是，人们使用符号数字策略是离散的，但不是连续的， 部分。最后，目标 3 将利用先前目标中获得的有关特定认知机制的见解来 测试关于如何支持幼儿的比例推理和概率推理的新颖预测 成人的决策（研究 5）。 候选人的长期目标是发展比例理论来解释一系列行为 背景和跨发展。指导阶段将在芝加哥大学心理学系进行 部门和拟议的理论构建、婴儿方法（目标 1）和计算建模培训 方法（目标 2）将使候选人处于成为方法论和理论专家的绝佳位置 认知发展领域的领导者。