Air Pollution Visualizations for Promoting Data Literacy with Middle Schoolers and the Public

空气污染是一个数据丰富的问题空间，有庞大的传感器网络不断捕获和报告测量结果。测量的污染物表面上对许多人来说很熟悉，但很少有人了解任何一种污染物的具体来源、可接受的水平和负面影响。此外，正规学校课程中关于空气质量的内容有限。该项目旨在通过公共信息亭加深公众对空气质量数据的认识，并通过青少年夏令营培养中学生对空气质量数据的认识。该项目将研究如何设计空气质量数据交互（通过两个并行设计：公共信息亭和青年夏令营），以支持学习者在数据调查、可视化和交流方面的个人代理，以及这些经验如何帮助非专家了解他们的环境。该项目扩大了公众对空气质量数据的参与，其方式超出了空气质量指数（AQI）的简化度量。因为这项工作有可能缩小科学界和公众之间的知识差距，它可能是在减轻空气污染方面实施有意义变革的重要起点。这项为期四年的跨学科研究利用了学习科学、可视化、初中和高中STEM教育、教师学习和专业发展方面的专业知识，为非正式学习创造了两个设计空间，旨在提高科学数据推理的参与度和自我效能感。该项目将推进人类数据交互（HDI）设计方面的知识，并通过空气质量可视化支持环境数据素养。数据可视化与环境（DVE）夏令营将与当地中学科学教育者合作设计，并将邀请来自亚特兰大地区的中学生到佐治亚理工学院校园参加为期两周的赞助项目，在此期间，他们将与科学教育者和可视化专家一起收集，可视化和显示环境数据。这些资助营地的招募将优先考虑在科学领域服务不足和代表性不足的群体。通过首先使用空气质量数据，然后是他们自己选择的感兴趣的环境数据集，学生将参与科学实践，生成并提出有关当地环境的循证论证，以调查与他们自己的社区、文化和兴趣相关的项目。该项目将同时开发和迭代情境化空气质量时间表（ContAQT）平台，作为亚特兰大中城的公共数据展示，分解当前和历史的当地多污染物空气质量数据。该项目将回答以下研究问题：(1)非正式环境中的数据交互如何支持对数据解释和环境的学习？(2)如何设计数据交互以支持学习者有机会调查个人感兴趣的问题？(3)哪些设计特征支持非专业学习者的数据探索？通过基于设计的研究，团队将调查界面和交互的变化如何影响数据流畅性指标，如统计推理谈话（识别异常值，趋势推理等），与先验知识的联系，以及提出问题。使用定性研究方法，如猜想映射，该项目将调查数据交互，简单地说，自由选择的公共信息亭交互（ContAQT）以及扩展的数据调查（夏令营）如何帮助学习者提出问题，与现有知识建立联系，提出和评估索赔。这项工作将促进以下领域的知识：1)构建科学数据的最佳实践，使非专业受众能够获得；2)理解可视化界面和交互中的特定设计决策如何影响数据交互和学习对话；3)设计夏令营活动，支持中学生发展数据流畅性和提高科学自我效能感；4)将科学教育者的知识综合为最佳实践，以吸引女性、黑人和/或拉丁学习者参与数据实践。该项目由推进非正式STEM学习（AISL）计划资助，该计划旨在推进非正式环境中STEM学习的设计和开发的新方法和基于证据的理解。这包括提供多种途径，扩大STEM学习经验的获取和参与，推进非正式环境中STEM学习的创新研究和评估，以及发展参与者对深度学习的理解。该奖项反映了美国国家科学基金会的法定使命，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。

Air pollution is a data-rich problem space, with vast networks of sensors constantly capturing and reporting measurements. The measured pollutants are superficially familiar to many people, but few understand the specific sources, acceptable levels, and negative effects of any individual pollutant. In addition, coverage of air quality in formal school curricula is limited. This project seeks to deepen the public's understanding of air quality data through a public kiosk and to develop middle schoolers' understanding of air quality data through a youth summer camp. The project will investigate how air quality data interactions (via these two concurrent designs: the public kiosk and the youth summer camp) can be designed to support learners' personal agency in data investigations, visualizations, and communications as well as how these experiences help non-experts learn about their environment. This project expands public engagement with air quality data in ways that extend beyond the simplified metric of the Air Quality Index (AQI). Because this work has the potential to lessen the knowledge gap between the scientific community and the general public it could be an important starting point for enacting meaningful change in mitigating air pollution.This four-year interdisciplinary effort draws on expertise in the learning sciences, visualization, middle and high school STEM education, and teacher learning and professional development to create two design spaces for informal learning aimed toward advancing engagement and self-efficacy in reasoning with scientific data. This project will advance knowledge in human-data interaction (HDI) design and support environmental data literacy through air quality visualizations. The Data Visualization and the Environment (DVE) summer camp will be designed in collaboration with local middle school science educators and will invite middle school students from the Atlanta area to Georgia Tech's campus for a sponsored 2-week program during which they will engage with science educators and visualization experts to collect, visualize, and display environmental data. Recruitment for these funded camps will prioritize underserved and underrepresented groups in science. By working first with air quality data and then a self-selected environmental dataset of interest to them, students will participate in the scientific practices of generating and presenting evidence-based arguments about their local environment to investigate projects of relevance to their own community, culture, and interests. The project will concurrently develop and iterate the Contextualized Air Quality Timelines (ContAQT) platform as a public data display in Midtown Atlanta breaking down current and historical local multipollutant air quality data. The project will answer the following research questions: (1) How can data interactions in informal settings support learning about data interpretations and the environment? (2) How can data interactions be designed to support learners' opportunities to investigate questions of personal interest? and (3) What design features support data exploration by non-expert learners? Through design-based research the team will investigate how changes to the interface and interaction impact data fluency indicators such as statistical reasoning talk (identifying outliers, reasoning about trends, etc.), connections to prior knowledge, and asking questions. Using qualitative research methods, such as conjecture mapping, the project will investigate how data interactions in brief, free-choice public kiosk interactions (ContAQT) as well as extended data investigations (summer camp) can assist learners in asking questions, making connections to existing knowledge, and proposing and evaluating claims. This work will advance knowledge in the following areas: 1) best practices for framing scientific data to be accessible to lay audiences; 2) understanding of how specific design decisions in visualization interfaces and interactions can influence data interactions and learning talk; 3) design of summer camp activities to support middle school students in developing data fluency and increasing self-efficacy in science; 4) synthesizing knowledge from science educators in best practices for engaging female, Black, and/or Latine learners in data practices.This project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.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.