Computational and developmental investigations of children’s self-representations and learning decisions

儿童自我表征和学习决策的计算和发展研究

• 批准号: 2204106
• 负责人: Mika Asaba
• 金额: $ 13.8万
• 依托单位: Asaba, Mika
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2204106&HistoricalAwards=false
• 关键词: Computational; developmental; investigations; children; self

This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Drs. Julian Jara-Ettinger and Julia Leonard at Yale University, this postdoctoral fellowship award supports an early career scientist studying the development of children’s self-representations. Children’s understanding of the self––what they like, what they know, what they are good at––has a deep influence on their learning and achievement. However, we lack a clear understanding of how exactly children develop views of the self, how these views are affected by their social interactions, and how they impact important real-world behaviors, such as children’s learning decisions. This research will advance fundamental scientific knowledge on children’s self-representations by developing a formal, quantitative theory of how children revise self-representations in social contexts, and how these self-representations impact their learning.The studies will combine computational and developmental approaches to test the hypothesis that children rationally construct and revise self-representations by integrating their prior experiences with social interactions. First, we will build a computational model that combines self-observations (e.g., failures and successes) with social feedback (e.g., what others think of the self) to explain learning about the self in social contexts. This model will be exhaustively tested and refined through studies with adults and compared against published developmental findings on relevant work. Second, we will use our model and alternative lesioned models to generate and test quantitative predictions for the developmental trajectory of children’s (3- to 6-year-olds) reasoning about the self. These models will make different assumptions about children’s sensitivities to self-observations and social feedback and if and how they integrate these sources of information. Our developmental experiment will systematically vary children’s performance on toys and a teacher’s beliefs about their competence, and test how these inform important learning behaviors: children’s persistence and challenge-seeking. By integrating state-of-the-art computational and developmental methods, this project will shed light on a deeply important learning problem for children: who they are, and what they can do.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项是美国国家科学基金会社会、行为和经济科学（SBE）博士后研究奖学金（SPRF）计划的一部分。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在博士的赞助下。耶鲁大学的朱利安·贾拉-艾廷格和茱莉亚·伦纳德，这个博士后奖学金支持了一位研究儿童自我表征发展的早期职业科学家。孩子们对自我的理解——他们喜欢什么，他们知道什么，他们擅长什么——对他们的学习和成就有着深刻的影响。然而，我们对儿童的自我观究竟是如何形成的，这些观点是如何受到他们的社会互动的影响的，以及它们是如何影响重要的现实世界行为的，比如儿童的学习决策，缺乏清晰的认识。本研究将通过发展儿童在社会环境中如何修正自我表征以及这些自我表征如何影响他们的学习的形式化、定量理论，推进儿童自我表征的基础科学知识。这些研究将结合计算和发展的方法来检验儿童通过整合他们先前的经验和社会互动来理性地构建和修改自我表征的假设。首先，我们将建立一个计算模型，将自我观察（例如，失败和成功）与社会反馈（例如，他人对自我的看法）相结合，以解释在社会环境中学习自我。该模型将通过对成人的研究进行详尽的测试和完善，并与已发表的有关工作的发展发现进行比较。其次，我们将使用我们的模型和其他损伤模型来生成和测试儿童（3- 6岁）关于自我推理的发展轨迹的定量预测。这些模型将对儿童对自我观察和社会反馈的敏感性以及他们是否以及如何整合这些信息来源做出不同的假设。我们的发展实验将系统地改变儿童在玩具上的表现和教师对他们能力的看法，并测试这些因素如何影响重要的学习行为：儿童的坚持和寻求挑战。通过整合最先进的计算和发展方法，该项目将为孩子们揭示一个非常重要的学习问题：他们是谁，他们能做什么。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。