Collaborative Research: Using AI-enabled Smart Objects to Understand and Support Spatial Reasoning and Learning

协作研究：使用人工智能智能对象来理解和支持空间推理和学习

• 批准号: 2040421
• 负责人: David Uttal
• 金额: $ 32.54万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2040421&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; AI; enabled

Spatial thinking is the ability to understand and use information about locations to solve problems. Spatial thinking is critically important to achievement in STEM disciplines. Fortunately, spatial thinking is malleable, it responds to training and to life experiences that require people to use their spatial skills. This research will develop and assess an AI system that will facilitate young children’s spatial thinking. The system relies on a time-tested method for improving children’s spatial skills: block play. The major advancement is that the blocks will be “smart”, in that they can detect child-interactions by tracking movement, acceleration, rotation, and how different objects are placed and handled with respect to each other. By analyzing children’s building patterns, the researchers will use machine learning to highlight patterns of block building and to suggest strategies to children as they build that may result in higher levels of spatial thinking. The results may support a transformative change in how we support spatial thinking, and ultimately STEM learning, in young children.The project develops a transformative engineering concept of endowing smartness and internet connectivity to children’s toys and everyday classroom/playroom objects. Examples of such objects include playing blocks, toys, jigsaw puzzle pieces, etc. The objective is for those toys and objects to precisely record how a child interacts with them individually and in a group as parts of their play and learning process. Such data is recorded and collected wirelessly at very high temporal and spatial resolutions. The project also develops a family of emerging Artificial Intelligence based algorithms to analyze the smart object-generated data to find out specific patterns in children’s handling of those objects. Such patterns are then analyzed for evaluating spatial thinking and spatial intelligence, and how they evolve over time under different training regimens. The investigators will develop embedded computing tools, both hardware and software, as well as low power wireless communication mechanisms for realizing this transforming engineering concept of smart objects. For the long term, they envision introducing ubiquitous smartness into many everyday objects so that tracking and analysis of spatial intelligence can be seamless and highly scalable.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.

空间思维是能够理解和使用有关位置的信息来解决问题的能力。空间思维对于STEM学科的成就至关重要。幸运的是，空间思维是可延展的，它对需要人们使用空间技能的培训和生活经验做出响应。这项研究将开发和评估AI系统，该系统将促进幼儿的空间思维。该系统依赖于提高儿童空间技能的时间测试方法：块游戏。主要的进步是，这些块将是“智能的”，因为它们可以通过跟踪运动，加速，旋转以及如何将不同的对象彼此置于和处理不同的对象来检测儿童互动。通过分析儿童的建筑模式，研究人员将使用机器学习来突出建筑的模式，并向儿童提出策略，因为它们可能会导致更高水平的空间思维。结果可能会支持我们在幼儿中支持空间思维和最终STEM学习的变革性变化。该项目开发了一种变革性的工程概念，即赋予儿童玩具以及每天的课堂/游戏室对象，将智能和互联网连接赋予智能和互联网连接。此类对象的示例包括玩具块，玩具，拼图拼图等。目的是针对那些玩具和对象，以精确记录孩子如何单独地和小组中的一部分作为游戏和学习过程的一部分与它们进行互动。在非常高的临时和空间分辨率下，记录并无线收集此类数据。该项目还开发了一个基于人工智能的新兴算法，以分析智能对象生成的数据，以找出儿童处理这些物体的特定模式。然后分析此类模式，以评估空间思维和空间智能，以及它们如何在不同的训练方案下随着时间的推移而发展。调查人员将开发嵌入式计算工具，包括硬件和软件，以及低功率无线通信机制，以实现这种转换的智能对象的工程概念。从长远来看，他们设想每天将无处不在的智能引入许多物体中，以便对空间智能的跟踪和分析可以是无缝且高度可扩展的。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来通过评估来诚实地支持。