Longitudinal Research on the Links between Reasoning and Math
Longitudinal Research on the Links between Reasoning and Math
批准号:
9310035
负责人:
Ariel Starr
金额:
$5.71万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-04-01 至 2019-03-31
关键词:
Academic achievementAchievementAdolescentArithmeticBehaviorBehavioralBiological Neural NetworksBrainBrain regionChildChildhoodCognitionCognitiveCognitive ScienceComplexControl GroupsCross-Sectional StudiesDataData SetDevelopmentEducational InterventionExhibitsGoalsGrowthHealthInterventionInvestigationKnowledgeLearningLinkMathematicsMediatingMethodologyMethodsModernizationNational Institute of Child Health and Human DevelopmentNational Institute of Mental HealthNursery SchoolsOccupationalOccupationsOutcomeParietalPerformancePlayPopulationProblem SolvingReadinessResearchRoleRouteSTEM fieldSchoolsSocietiesTestingThinkingVariantagedbasebrain behaviorcognitive neurosciencecognitive skillcognitive trainingdevelopmental psychologyearly childhoodexecutive functionflexibilitygroup interventionimprovedinnovationinsightintervention effectkindergartenlongitudinal analysislongitudinal datasetmathematical abilitymultimodalitynovelpublic health relevancerelating to nervous systemskillsstandardize measurestemsuccesssupport networktherapy designtherapy development
中文摘要
描述(由申请人提供):在我们的信息驱动的社会中,数学能力是成功的关键,特别是在推动现代经济的STEM领域。然而,在人口中,数学能力存在很大差异,这种差异在正式学校教育的第一年就已经存在。此外,幼儿园的数学能力
这是孩子日后学业和职业成就的有力预测指标。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能力的途径,尽管它们取得的成功参差不齐。然而,推理能力,这是灵活解决问题的关键,并与数学能力密切相关,已收到相对较少的关注,尽管提高幼儿的推理能力可能是一个有前途的路线,以影响以后的数学表现的可能性。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,本申请的具体目标是识别支持推理和数学之间联系的认知技能和神经基质。目标1将测试特定认知技能集在数学成绩增长中的因果作用。学龄前儿童将接受以游戏为基础的干预,目标是推理能力或EF。该假设是,推理的增长将导致儿童的能力,以提高认识的数量级之间的顺序关系,这将导致更大的改善算术性能相对于EF为重点的干预。在推理任务的瞳孔测量指标将被用来调查儿童的顺序推理的时间动态,提供深入了解的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。这一目标利用了一个预先存在的纵向数据集,调查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。该假说认为,数学成绩的增长与推理发展中所涉及的额顶叶脑网络的功能活动和连通性的变化有关。总之,这些数据将告诉我们哪些干预目标对提高儿童的数学成绩最有效,并将提供对支持数学成绩增长的神经变化的见解。这种方法是创新的多模态方法,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,因为理解推理和数学之间的联系对于开发新的数学能力评估和教育干预措施以促进数学增长至关重要,这两者对于改善幼儿的入学准备和学习成绩都是必要的。
英文摘要
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.
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