Data Visualization Literacy: Research and Tools that Advance Public Understanding of Scientific Data

数据可视化素养：促进公众对科学数据理解的研究和工具

• 批准号: 1713567
• 负责人: Katy Borner
• 金额: $ 135.52万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1713567&HistoricalAwards=false
• 关键词: Data; Visualization; Literacy; Research; Tools

As the world is increasingly dependent upon computing and computational processes associated with data analysis, it is essential to gain a better understanding of the visualization technologies that are used to make meaning of massive scientific data. It is also essential that the infrastructure, the very means by which technologies are developed for improving the public's engagement in science itself, be better understood. Thus, this AISL Innovations in Development project will address the critical need for the public to learn how to interpret and understand highly complex and visualized scientific data. The project will design, develop and study a new technology platform, xMacroscope, as a learning tool that will allow visitors at the Science Museum of Minnesota and the Center of Science and Industry, to create, view, understand, and interact with different data sets using diverse visualization types. The xMacroscope will support rapid research prototyping of public experiences at selected exhibits, such as collecting data on a runner's speed and height and the visualized representation of such data. The xMacroscope will provide research opportunities for exhibit designers, education researchers, and learning scientists to study diverse audiences at science centers in order to understand how learning about data through the xMacroscope tool may inform definitions of data literacy. The research will advance the state of the art in visualization technology, which will have broad implications for teaching and learning of scientific data in both informal and formal learning environments. The project will lead to better understanding by science centers on how to present data to the public more effectively through visualizations that are based upon massive amounts of data. Technology results and research findings will be disseminated broadly through professional publications and presentations at science, education, and technology conferences. The 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.The project is driven by the assumption that in the digital information age, being able to create and interpret data visualizations is an important literacy for the public. The research will seek to define, measure, and advance data visualization literacy. The project will engage the public in using the xMacrocope at the Science Museum of Minnesota and at the Center of Science and Industry's (COSI) science museum and research center in Columbus, Ohio. In both museum settings the public will interact with different datasets and diverse types of visualizations. Using the xMacroscope platform, personal attributes and capabilities will be measured and personalized data visualizations will be constructed. Existing theories of learning (constructivist and constructionist) will be extended to capture the learning and use of data visualization literacy. In addition, the project team will conduct a meta-review related to different types of literacy and will produce a definition with performance measures to assess data visualization literacy - currently broadly defined in the project as the ability to read, understand, and create data visualizations. The research has potential for significant impact in the field of science and technology education and education research on visual learning. It will further our understanding of the nature of data visualization literacy learning and define opportunities for visualizing data in ways that are both personally and culturally meaningful. The project expects to advance the understanding of the role of personalization in the learning process using iterative design-based research methodologies to advance both theory and practice in informal learning settings. An iterative design process will be applied for addressing the research questions by correlating visualizations to individual actions and contributions, exploring meaning-making studies of visualization construction, and testing the xMacroscope under various conditions of crowdedness and busyness in a museum context. The evaluation plan is based upon a logic model and the evaluation will iteratively inform the direction, process, and productivity of the project.

由于世界越来越依赖于与数据分析相关的计算和计算过程，因此有必要更好地理解用于解释大量科学数据的可视化技术。同样重要的是，基础设施——开发技术以提高公众对科学本身的参与的手段——也必须得到更好的理解。因此，这个AISL创新发展项目将解决公众学习如何解释和理解高度复杂和可视化科学数据的关键需求。该项目将设计、开发和研究一个新的技术平台xMacroscope，作为一种学习工具，允许明尼苏达科学博物馆和科学与工业中心的游客使用不同的可视化类型来创建、查看、理解和交互不同的数据集。xMacroscope将支持选定展览中公众体验的快速研究原型，例如收集跑步者的速度和高度数据以及这些数据的可视化表示。xMacroscope将为展览设计师、教育研究人员和学习科学家提供研究机会，研究科学中心的不同受众，以了解通过xMacroscope工具学习数据如何影响数据素养的定义。这项研究将推动可视化技术的发展，这将对非正式和正式学习环境中科学数据的教学产生广泛的影响。该项目将使各科学中心更好地了解如何通过基于大量数据的可视化更有效地向公众展示数据。技术成果和研究成果将通过专业出版物和在科学、教育和技术会议上的报告广泛传播。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。该项目是基于这样一个假设：在数字信息时代，能够创建和解释数据可视化是公众的一项重要素养。该研究将寻求定义、测量和推进数据可视化素养。该项目将让公众在明尼苏达州科学博物馆和俄亥俄州哥伦布市科学与工业中心（COSI）科学博物馆和研究中心使用xMacrocope。在这两个博物馆设置中，公众将与不同的数据集和不同类型的可视化交互。使用xMacroscope平台，将测量个人属性和能力，并构建个性化的数据可视化。现有的学习理论（建构主义和建构主义）将被扩展，以捕捉数据可视化素养的学习和使用。此外，项目团队将进行一项与不同类型的读写能力相关的元审查，并将产生一个带有评估数据可视化读写能力的性能指标的定义——目前在项目中被广泛定义为阅读、理解和创建数据可视化的能力。该研究在科学技术教育和视觉学习教育研究领域具有重要的影响潜力。它将进一步加深我们对数据可视化素养学习本质的理解，并定义以对个人和文化都有意义的方式可视化数据的机会。该项目希望通过基于设计的迭代研究方法，促进对个性化在学习过程中的作用的理解，从而在非正式学习环境中推进理论和实践。通过将可视化与个人行为和贡献相关联，探索可视化构建的意义研究，并在博物馆环境中拥挤和繁忙的各种条件下测试xMacroscope，将采用迭代设计过程来解决研究问题。评估计划基于逻辑模型，并且评估将迭代地告知项目的方向、过程和生产力。

项目成果

Visualizing learner engagement, performance, and trajectories to evaluate and optimize online course design

• DOI: 10.1371/journal.pone.0215964
• 发表时间: 2019-05-06
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Ginda, Michael;Richey, Michael C.;Borner, Katy
• 通讯作者: Borner, Katy

Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy

• DOI: 10.1073/pnas.1804247115
• 发表时间: 2018-12-11
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Boerner, Katy;Scrivner, Olga;Evans, James A.
• 通讯作者: Evans, James A.

The impact of air transport availability on research collaboration: A case study of four universities

• DOI: 10.1371/journal.pone.0238360
• 发表时间: 2018-11
• 期刊: PLoS ONE
• 影响因子: 3.7
• 作者: Adam Ploszaj;Xiaoran Yan;K. Börner

Cultivating data visualization literacy in museums

培养博物馆数据可视化素养

• DOI: 10.1108/ils-04-2020-0132
• 发表时间: 2021
• 期刊: Information and Learning Sciences
• 影响因子: 3.4
• 作者: Peppler, Kylie;Keune, Anna;Han, Ariel
• 通讯作者: Han, Ariel

Job postings in the substance use disorder treatment related sector during the first five years of Medicaid expansion

• DOI: 10.1371/journal.pone.0228394
• 发表时间: 2020-01-30
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Scrivner, Olga;Nguyen, Thuy;Borner, Katy
• 通讯作者: Borner, Katy