CRII:HCC: A Crowdsourced Social Computing Platform with Gamification Mechanisms for Healthy Eating

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This project focuses on inequity in access to educative health information. Better health awareness can help people reduce obesity, diabetes, and other chronic conditions, but some of the communities most at risk of these conditions have limited access to the nutritional expertise needed to develop that awareness. To do this, the research team will design and test several systems that provide both individual practice and social interaction around nutrition topics. These interfaces will allow people to specify their own health goals, connect people with like-minded peers, and provide motivational elements, with the aim of increasing access to nutritional information and building communities of peers eager to share knowledge and translate it into behavioral changes that help them accomplish their goals. The work will also provide opportunities at the intersection of computer science and design for students who are historically underrepresented in computer science.To meet these goals, the proposal will explore new approaches to social computing mechanisms that blend together the motivational benefits of judiciously chosen gamification features with the benefits of crowdsourcing and online learning environments. Specifically, the project team will develop new crowdsourced, learner-centered nutrition games that help users develop nutritional evaluation skills through assessing nutritional content of the crowd's meals and receiving the crowd's feedback. The work aims at three specific contributions. The first is exploring new models for aggregating and presenting crowdsourced intelligence in the nutrition context, by embedding a Community Board inside a game environment that hosts "in-the-wild" meal photographs that are evaluated by peers about their fit to the poster's nutritional goals. The second is leveraging people's use of the system to create a well-annotated dataset of meal photographs and nutrition information that can fuel research on computer vision techniques for assessing nutritional content of food photos. The third is identifying ways in which this crowdsourced Community Board can be effectively used and assessed as a learning tool for populations with low nutritional literacy.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.