Complex systems such as combustion engines and the human body are made up of interrelated components that form a holistic, interdependent system. Despite their pervasiveness in everyday life, complex systems are challenging for children to learn and for educators to teach. Prior work has shown that students struggle to understand how individual parts of a system affect the system’s operation as a whole, narrowly focus on visible aspects like a system’s structure, and have limited access to real examples that could affirm or contradict their understanding.
We introduce PrototypAR, an AR-based “smart desk” that allows children to prototype complex systems using familiar paper craft, to learn about and correct design mistakes via real-time AR-based feedback, and to test their creations in a digital simulation environment. Our overarching goal is to explore how AR and emerging techniques in computer vision and the learning sciences can be combined to engage children in novel STEM learning experiences.
