Longitudinal Research on the Links between Reasoning and Math

推理与数学联系的纵向研究

• 批准号: 9310035
• 负责人: Ariel Starr
• 金额: $ 5.71万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9310035
• 关键词: Academic achievement; Achievement; Adolescent; Arithmetic; Behavior; Behavioral; Biological Neural Networks; Brain; Brain region; Child; Childhood; Cognition; Cognitive; Cognitive Science; Complex; Control Groups; Cross-Sectional Studies; Data; Data Set; Development; Educational Intervention; Exhibits; Goals; Growth; Health; Intervention; Investigation; Knowledge; Learning; Link; Mathematics; Mediating; Methodology; Methods; Modernization; National Institute of Child Health and Human Development; National Institute of Mental Health; Nursery Schools; Occupational; Occupations; Outcome; Parietal; Performance; Play; Population; Problem Solving; Readiness; Research; Role; Route; STEM field; Schools; Societies; Testing; Thinking; Variant; aged; base; brain behavior; cognitive neuroscience; cognitive skill; cognitive training; developmental psychology; early childhood; executive function; flexibility; group intervention; improved; innovation; insight; intervention effect; kindergarten; longitudinal analysis; longitudinal dataset; mathematical ability; multimodality; novel; public health relevance; relating to nervous system; skills; standardize measure; stem; success; support network; therapy design; therapy development

 DESCRIPTION (provided by applicant): In our information-driven society, math ability is essential for success, particularly in the STEM fields that drive the modern economy. Within the population, however, there exist large variations with regard to math ability, and this variabilityis already present in the first year of formal schooling. Furthermore, math ability in kindergarten is a strong predictor of a child's later academic and professional achievement. Many interventions have focused on executive functions (EFs) and early number knowledge as routes to improve preschool-aged children's math proficiency, though they have been met with mixed success. However, reasoning ability, which is critical for flexible problem solving and correlates strongly with math ability, has received relatively little focus despite the possibility that improving reasoning ability in young children may be a promising route to impacting later math performance. The NICHD strives to develop more personalized and effective cognitive interventions. In line this with this goal, the specific objective of this application is to identiy the cognitive skills and neural substrates that support the link between reasoning and math. Aim 1 will test the causal role of specific cognitive skill sets in the growth of math achievement. Preschool-aged children will receive game- based interventions that target either reasoning ability or EFs. The hypothesis is that growth in reasoning will lead to improvements in children's ability to recognize ordinal relations between numerical magnitudes, which will result in greater improvements in arithmetic performance relative to the EF-focused intervention. Pupillometry metrics during a reasoning task will be used to investigate the temporal dynamics of children's ordinal reasoning, providing insight into the mechanisms of change promoted by the interventions. Aim 2 will characterize the links between reasoning ability, math achievement, and brain function in children aged 6-19 years. This aim takes advantage of a preexisting longitudinal dataset investigating the neural and cognitive factors that support reasoning development. The NIMH aims to understand the neural bases of complex behaviors. The hypothesis is that growth in math performance will be related to changes in functional activity and connectivity within the fronto-parietal brain networks implicated in reasoning development. Together, these data will tell us which targets of intervention are most effective at improving children's math performance and will provide insight into the neural changes that support growth in math performance. This approach is innovative it its multimodal methodology, because it combines methods from developmental psychology, cognitive psychology, and cognitive neuroscience in order to improve our understanding of the factors that promote growth in math ability. The proposed research is significant because understanding the connection between reasoning and math is critical for the development of novel assessments of math ability and educational interventions to promote growth in math, both of which are necessary to improve school readiness and academic performance in young children.

 描述（由申请人提供）：在我们这个信息驱动的社会中，数学能力对于成功至关重要，特别是在推动现代经济的 STEM 领域。然而，在人群中，数学能力存在很大差异，这种差异在正规学校教育的第一年就已经存在。此外，幼儿园的数学能力 是孩子以后学业和职业成就的有力预测者。许多干预措施都侧重于执行功能（EF）和早期数字知识，作为提高学龄前儿童数学水平的途径，尽管这些干预措施的成功程度参差不齐。然而，推理能力对于灵活解决问题至关重要，并且与数学能力密切相关，尽管提高幼儿的推理能力可能是影响以后数学表现的一条有希望的途径，但它受到的关注相对较少。 NICHD 致力于开发更加个性化和有效的认知干预措施。与此目标一致，该应用程序的具体目标是确定支持推理和数学之间联系的认知技能和神经基础。目标 1 将测试特定认知技能对数学成绩增长的因果作用。学龄前儿童将接受以推理能力或 EF 为目标的基于游戏的干预措施。假设推理能力的提高将提高儿童识别数值大小之间顺序关系的能力，这将导致相对于以 EF 为重点的干预而言，算术表现有更大的提高。推理任务期间的瞳孔测量指标将用于调查儿童顺序推理的时间动态，从而深入了解干预措施促进的变化机制。目标 2 将描述 6-19 岁儿童的推理能力、数学成绩和大脑功能之间的联系。这一目标利用了现有的纵向数据集来研究支持推理发展的神经和认知因素。 NIMH 旨在了解复杂行为的神经基础。该假设认为，数学成绩的增长与推理发展所涉及的额顶叶大脑网络的功能活动和连接性的变化有关。总之，这些数据将告诉我们哪些干预目标对于提高儿童的数学成绩最有效，并将深入了解支持数学成绩增长的神经变化。这种方法的多模态方法是创新的，因为它结合了发展心理学、认知心理学和认知神经科学的方法，以提高我们对促进数学能力增长的因素的理解。这项研究意义重大，因为了解推理和数学之间的联系对于开发新颖的数学能力评估和促进数学成长的教育干预措施至关重要，而这两者对于提高幼儿的入学准备和学习成绩都是必要的。