A large-scale investigation into the foundations and development of social cognition

该奖项是作为NSF社会、行为和经济科学(SBE)博士后研究奖学金(SPRF)计划的一部分提供的。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职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项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。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在麻省理工学院的劳拉·舒尔茨博士和哈佛大学的伊丽莎白·博纳维茨博士的赞助下，这一博士后奖学金奖项支持一位早期职业科学家研究儿童对他人思维的理解是如何发展的。要分享我们所知道的，向他人学习，一起工作，甚至进行简单的对话，我们需要考虑其他人的心理状态--他们的目标、愿望、知识和信念。这种社会认知能力能够理解别人的想法，并对他们的心理状态进行推理，这种能力在整个学龄前几年都会成熟。然而，尽管这些能力对于教、学和基本交流很重要，但它们是如何出现的仍然不完全清楚。相反，最近的研究揭开了一个谜团：尽管学龄前儿童很早就掌握了目标、偏好和欲望等心理状态，但他们往往很难推理出其他人知道或相信什么。为了研究心理状态推理的不同方面是如何出现的，这个项目将利用计算方法来阐明不同心理状态推理任务所需的认知能力，并验证更新的心理状态推理电池以评估每种能力的发展。然后，该项目将利用大规模在线发展科学的最新进展，对具有代表性的大样本儿童进行这种电池管理。具体地说，NSF资助的在线摇篮基础设施将使该项目能够收集前所未有的丰富和规模的数据，从世界各地的参与者那里收集数据，并轻松地纵向跟踪参与者。通过这个项目，研究员将开发用于在线数据收集的新工具和管道，并将评估这些新方法是否使研究人员能够招募更具代表性的样本。这些进展将对发展科学领域产生广泛的作用。通过更多地了解人类社会认知的发展，我们可以更好地理解是什么让人类成为如此优秀的教师、学习者和沟通者。这些信息可以帮助研究人员继续改进教育政策，帮助临床医生更好地帮助那些在精神状态推理方面苦苦挣扎的人，并使科学家能够设计能够更好地与人类互动的人工智能。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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 (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 Dr. Laura Schulz at MIT and Dr. Elizabeth Bonawitz at Harvard, this postdoctoral fellowship award supports an early career scientist examining how children’s understanding of other minds develops. To share what we know, learn from others, work together, and conduct even simple conversations, we need to consider other people’s mental states—their goals, desires, knowledge, and beliefs. This social cognitive ability to figure out what other people are thinking, and reason about their mental states, matures throughout the preschool years. However, despite the importance of these capacities for teaching, learning, and basic communication, it is still not fully clear how they emerge. Instead, recent work has uncovered a puzzle: while preschoolers have an early grasp of mental states like goals, preferences and desires, they often struggle to reason about what others know or believe. To investigate how different aspects of mental state reasoning emerge, this project will leverage a computational approach to clarify the cognitive capacities required for different mental state reasoning tasks, and validate an updated mental state reasoning battery to assess the development of each capacity. The project will then leverage recent advances in large-scale online developmental science to administer this battery to a large and representative sample of children. Specifically, the NSF-funded online CRADLE infrastructure will enable the project to collect data of unprecedented richness and scale, collecting data from participants worldwide, and following participants longitudinally with ease. Through this project, the fellow will develop new tools and pipelines for online data collection, and will assess whether these new methods enable researchers to recruit more representative samples. These advances will be of broad use to the field of developmental science. By learning more about the development of human social cognition, we can better understand what makes humans such uniquely good teachers, learners, and communicators. This information can help researchers continue improving educational policy, help clinicians better assist individuals who struggle with mental state reasoning, and enable scientists to design artificial intelligences that can better interact with humans.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.