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

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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.