Testing a Framework of Environmental Adaptation in Children's Learning Strategies

测试儿童学习策略中的环境适应框架

• 批准号: 10701850
• 负责人: Katherine Adams Shannon
• 金额: $ 7.2万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2024-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10701850
• 关键词: 6 year old; Address; Adult; Age; Behavior; Biological Models; Child; Child Behavior; Complex; Computer Models; Computing Methodologies; Costs and Benefits; Data; Decision Making; Education; Environment; Exposure to; Feedback; Future; Goals; Home environment; Intervention; Investigation; Lead; Learning; Mediating; Modeling; Outcome; Research Personnel; Rewards; Risk; Series; Shapes; Social Environment; Social support; Testing; Toy; Work; caregiving; cost; design; early life adversity; environmental adaptation; environmental change; experience; experimental study; help-seeking behavior; high reward; improved; insight; learning outcome; learning strategy; novel; peer; predictive modeling; response; social; social learning; supportive environment; theories

PI/PD: Katherine Adams Shannon PROJECT SUMMARY How do children learn within their early social environments? An important factor in social learning is the responsiveness or reliability of help from social partners. Children who experience unresponsive or inconsistent caregiving may often have their bids for help go unanswered; other children may experience different social partners who vary in their helpfulness. Despite its ramifications for long-term learning outcomes, we still understand little about how young children adapt their learning strategies as a function of the reliability of help in their social environments, and how such adaptations shape learning outcomes. The goal of the current proposal is to develop and test a framework that describes environmental adaptation in children’s learning strategies. In a series of experiments with 4- to 6-year-olds, we start with a simple design that operationalizes ‘reliability of help’ as whether or not a social partner consistently responds to or ignores bids for help before children complete a learning task (e.g., figure out how a toy works). Within this experimental setting, we address 3 specific aims: In Aim 1, we ask if children adapt their (1) learning goals and (2) decisions to explore alone or seek help based on the past helpfulness of a social partner, and if so, whether these adaptations maximize learning outcomes given the likelihood of receiving help. A given behavior is adaptive if it benefits learning in one social environment, but the same behavior can lead to costs in another. It follows that a beneficial learning adaptation can become maladaptive if the conditions of the environment change. In Aim 2, we introduce a reliable-to-unreliable and unreliable-to-reliable change in the reliability of help, such that a social partner who was helpful before learning stops responding to children’s bids for help (and vice versa). Here, we test whether an environmental change can lead children to use mismatched learning strategies that, in turn, lead to suboptimal learning outcomes. In Aim 3, we construct a computational model that describes environmental adaptation in children’s learning strategies according to the principles of utility-based social reasoning, wherein children consider the behavior of their social partners to maximize the expected utility (i.e., benefits net of costs) of a given learning decision. We test model predictions against children’s behavior in the experiments. Taken together, this work will provide key empirical data and a computational model to advance our understanding of how children learn within diverse social contexts. The long-term objective of this proposal is to generate novel insights into the ways in which children, particularly those who live in less supportive environments, make decisions during social learning that shape their future learning outcomes. Findings have promise to inform interventions that improve social learning interactions as a means to support early education.

PI/PD: Katherine Adams Shannon

项目成果

iCatcher+: Robust and Automated Annotation of Infants' and Young Children's Gaze Behavior From Videos Collected in Laboratory, Field, and Online Studies.

• DOI: 10.1177/25152459221147250
• 发表时间: 2023-04
• 期刊: ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE
• 影响因子: 13.6
• 作者: Erel, Yotam;Shannon, Katherine Adams;Chu, Junyi;Scott, Kim;Struhl, Melissa Kline;Cao, Peng;Tan, Xincheng;Hart, Peter;Raz, Gal;Piccolo, Sabrina;Mei, Catherine;Potter, Christine;Jaffe-Dax, Sagi;Lew-Williams, Casey;Tenenbaum, Joshua;Fairchild, Katherine;Bermano, Amit;Liu, Shari
• 通讯作者: Liu, Shari

Associations between early efficiency in language processing and language and cognitive outcomes in children born full term and preterm: similarities and differences.

足月和早产儿的早期语言处理效率与语言和认知结果之间的关联：相似点和差异。

• DOI: 10.1080/09297049.2022.2138304
• 发表时间: 2023
• 期刊: Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence
• 作者: Marchman,VirginiaA;Ashland,MelanieD;Loi,ElizabethC;Munevar,Mónica;Shannon,KatherineA;Fernald,Anne;Feldman,HeidiM
• 通讯作者: Feldman,HeidiM