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

该项目的重点是在获得教育性卫生信息方面的不平等。 更好的健康意识可以帮助人们减少肥胖，糖尿病和其他慢性疾病，但一些最有可能患上这些疾病的社区获得发展这种意识所需的营养专业知识的机会有限。为此，研究小组将设计和测试几个系统，围绕营养主题提供个人实践和社会互动。这些接口将允许人们指定自己的健康目标，将人们与志同道合的同龄人联系起来，并提供激励因素，目的是增加获得营养信息的机会，建立渴望分享知识并将其转化为行为变化的同龄人社区，帮助他们实现目标。这项工作还将为计算机科学和设计的交叉点提供机会，为历史上在计算机科学中代表性不足的学生提供机会。为了实现这些目标，该提案将探索社会计算机制的新方法，将明智选择的游戏化功能的激励优势与众包和在线学习环境的优势融合在一起。具体来说，项目团队将开发新的众包、以学习者为中心的营养游戏，通过评估人群膳食的营养成分，并接收人群的反馈，帮助用户培养营养评估技能。 这项工作的目标是三个具体的贡献。 第一个是探索在营养背景下聚合和呈现众包情报的新模式，通过将社区委员会嵌入游戏环境中，该环境中包含“野外”用餐照片，由同行评估其是否符合海报的营养目标。 第二个是利用人们对该系统的使用来创建一个注释良好的膳食照片和营养信息数据集，这可以推动计算机视觉技术的研究，以评估食物照片的营养成分。 第三个是确定如何有效地使用和评估这一众包社区委员会，作为营养知识水平低的人群的学习工具。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.