Investigating the cognitive mechanisms underlying children's question asking

该奖项是作为NSF的社会，行为和经济科学博士后研究奖学金（SPRF）计划的一部分提供的。SPRF计划的目标是为学术界，工业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的奖励包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在纽约大学的托德古雷基斯博士和马乔里罗兹博士的赞助下，这个博士后奖学金支持一位早期职业科学家调查使儿童能够提出有效问题的认知机制。提问是学习的关键工具，尤其是在儿童时期，但是提出一个信息性的问题一个能引出新的有用信息的问题通常是困难的。研究儿童如何提出信息性问题将促进对人类如何指导自己学习的科学理解。这将对教育环境产生影响，因为学生往往无法提出有效的问题。此外，通过了解人类如何引导自己的学习，研究人员将能够更好地设计做同样事情的机器-这是人工智能的一个重要问题。本项目将开发和测试一个新的提问帐户，灵感来自最近的决策和解决问题的研究。该账户描绘了学习者可能采取的多条路线来生成候选问题并在它们之间进行评判，并在最终提出的问题的信息量和计算成本之间进行权衡（例如，时间、认知努力）与生成和选择该问题相关联。本研究将采用多方法研究方法，测试（1）是否有证据表明2至10岁儿童的问题提问有多种途径，以及（2）儿童如何在问题信息量和计算成本之间进行权衡。特别是，本研究将分析现有的语料库的自然亲子对话，以测试儿童的问题是如何塑造他们的父母以前的问题和答案，它将开发新的实验范式，以调查儿童如何以及何时创新的新颖，信息丰富的问题。这项研究的结果将揭示父母的问题和答案，儿童的概念知识和计算考虑如何在一系列设置中告知儿童的问题。因此，该项目将朝着理解问题背后的复杂认知机制迈出重要一步--问题是一种提高人类智力和创造力并对学习做出重要贡献的技能。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award was provided as part of NSF's Social, Behavioral and Economic Sciences 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 Dr. Todd Gureckis and Dr. Marjorie Rhodes at New York University, this postdoctoral fellowship award supports an early career scientist investigating the cognitive mechanisms that enable children to ask effective questions. Question asking is a key tool for learning, especially in childhood, but coming up with an informative question—one that will elicit new and useful information—is often difficult. Studying how children ask informative questions will advance scientific understanding of how humans guide their own learning. This will have implications in educational settings, where students often fail to ask effective questions. Moreover, by understanding how humans guide their own learning, researchers will be better able to desig machines that do the same—an important problem for Artificial Intelligence.The present project will develop and test a new account of question asking, inspired by recent research on decision making and problem solving. This account delineates multiple routes a learner might take to generate candidate questions and adjudicate between them, with a tradeoff between the informativeness of the question that is ultimately asked and the computational costs (e.g., time, cognitive effort) associated with generating and selecting this question. Using a multi-method approach, this research will test (1) whether there is evidence for these multiple routes to question asking in 2- to 10-year-old children, and (2) how children navigate the tradeoff between question informativeness and computational cost. In particular, this research will analyze an existing corpus of naturalistic parent-child conversation to test how children’s questions are shaped by their parents’ previous questions and answers, and it will develop new experimental paradigms to investigate how and when children innovate novel, informative questions. The results from this research will shed new light on how parents' questions and answers, children's conceptual knowledge, and computational considerations inform children’s question asking in a range of settings. As a result, this project will take a significant step towards an understanding of the complex cognitive mechanisms that underlie question asking—a skill that exemplifies human intelligence and creativity and makes important contributions to learning.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.