SBIR-STTR Award

An augmented learning platform for mobile devices
Award last edited on: 2/28/2017

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,405,730
Award Phase
2
Solicitation Topic Code
EA
Principal Investigator
Tarun Pondicherry

Company Information

LightUp Inc

2660 South El Camino Real
San Mateo, CA 94403
   (732) 705-1198
   hello@lightup.io
   www.lightup.io
Location: Single
Congr. District: 18
County: Santa Clara

Phase I

Contract Number: 1520594
Start Date: 7/1/2015    Completed: 12/31/2015
Phase I year
2015
Phase I Amount
$150,000
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.

Phase II

Contract Number: 1632721
Start Date: 8/1/2016    Completed: 7/31/2018
Phase II year
2016
(last award dollars: 2019)
Phase II Amount
$1,255,730

This Phase II project is to the first personalized learning platform for hands-on education that works with the billions of mobile devices already in people's hands worldwide. Because the technology works on any mobile device and requires little instructor facilitation, it will be commercially successful in home settings when parents are busy and school settings where budget restrictions limit the number of facilitators. Beyond commercial impact, this project will help address the nation's need to prepare citizens for the 21st century economy, improve science literacy and help provide equal opportunities to underrepresented minorities in science, technology, engineering and mathematics (STEM). This project is an effective teaching tool because it employs personalized learning, where the content and pace of learning are optimized for the individual learner. Personalized learning has already been shown to result in higher learner engagement and increased retention of concepts in educational software. Through the use of proprietary augmented reality and adaptive learning technology, this project brings personalized learning to hands-on STEM education, enabling learners to develop problem solving skills in a more effective, engaging and lower cost way.The key innovation in this project is a single software framework combining advanced augmented reality (AR) and adaptive learning (AL) techniques to capture learners? interactions with real world objects (for example, circuit blocks, fraction bricks or chemistry models) via a mobile device camera, analyze the significance of the interactions and automatically provide personalized guidance to each learner. The system will be the first to provide a high level API above the complexity of AR and AL, allowing designers of learning experience modules to focus solely on content and user experience instead of hundreds of thousands of lines of complex code associated with AR and AL. The methods employed will be the research, design and development of the augmented reality and adaptive learning engine, its integration with three learning experience modules: circuits, fractions, basic geometry, and an evaluation of the modules. To guide the development, pilot studies utilizing A/B testing with competing approaches, pre and post assessments, and behavioral analysis of users interacting with the system will be conducted periodically.