SBIR Phase I: An augmented learning platform for mobile devices

This SBIR Phase I project will develop and test the software foundation for a novel augmented learning platform enabled by today's mobile devices. While research has shown that project-based learning is crucial for children to understand science, technology, engineering and math (STEM) topics, it currently requires knowledgeable facilitators providing guidance to be effective. This greatly limits the feasibility of project-based learning in schools, homes and informal learning environments. Augmented learning platforms hold the potential to change this, but are not widely deployed because they typically require expensive and unwieldy table top displays. The technology being developed in this project turns any mobile device into an augmented learning platform, transforming ordinary hands-on learning environments into interactive experiences by enhancing them with digital information. This project aligns with the National Science Foundation's mission to support science and engineering education at all levels by developing a novel educational platform that opens up STEM topics to all children, regardless of their prior experience or learning environment. The smart education and learning market is valued at $122 billion (2014), meaning that the commercial success of this U.S.-based company selling through U.S. schools and retailers will positively impact both domestic tax revenue and jobs. The augmented learning platform that will be developed in this project will enable project-based learning at an unprecedented scale. The platform will perform three tasks. It will employ computer vision to detect electronic circuits and convert them into a graph data structure. Then, it will use artificial intelligence and simulation to analyze the resulting graph data structure. Finally, it will provide feedback to users with an augmented reality overlay within a few milliseconds. The goal of the research is to develop and test this platform with the company's current users by integrating it into an electrical engineering tutor app and evaluating their engagement and learning outcome compared to pure hardware or software systems that teach engineering concepts. The system will initially be tested with data from automated mobile analytics tools from a wide-scale deployment to current users of the electrical engineering tutor app. In the future, the underlying technology can work with any subject that produces a graph data structure for analysis. The novel platform in this project enables every mobile device to be a learning platform, giving millions access to project-based learning.