Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments
Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments
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DOI：
10.1073/pnas.1807180116
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发表时间：
2019-02-05
影响因子：
11.1
通讯作者：
Ginda, Michael
中科院分区：
文献类型：
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作者：
Boerner, Katy;Bueckle, Andreas;Ginda, Michael
在信息时代，阅读和构建数据可视化的能力变得与阅读和编写文本的能力一样重要。然而，虽然存在用于教授和评估文本素养、数学素养和视觉素养的标准定义和理论框架，但目前的数据可视化素养（DVL）定义和框架还不够全面，无法指导DVL教学和评估的设计。本文介绍了一个数据可视化素养框架（DVL- fw），它是专门为定义、教授和评估DVL而开发的。整体的DVL-FW促进了数据可视化的阅读和构建，这一配对类似于文本素养中的阅读和写作以及数学素养中的理解和应用。具体来说，DVL-FW定义了核心概念的分层类型，并详细说明了从数据中提取见解所需的流程步骤。DVL- fw将理论知识和程序知识联系起来，并展示了如何将两者结合起来设计DVL的课程和评估措施。早期版本的DVL- fw已经被用于向8500多名住校和在线学生教授DVL，这项工作的结果有助于修改和验证本文介绍的DVL- fw。
In the information age, the ability to read and construct data visualizations becomes as important as the ability to read and write text. However, while standard definitions and theoretical frameworks to teach and assess textual, mathematical, and visual literacy exist, current data visualization literacy (DVL) definitions and frameworks are not comprehensive enough to guide the design of DVL teaching and assessment. This paper introduces a data visualization literacy framework (DVL-FW) that was specifically developed to define, teach, and assess DVL. The holistic DVL-FW promotes both the reading and construction of data visualizations, a pairing analogous to that of both reading and writing in textual literacy and understanding and applying in mathematical literacy. Specifically, the DVL-FW defines a hierarchical typology of core concepts and details the process steps that are required to extract insights from data. Advancing the state of the art, the DVL-FW interlinks theoretical and procedural knowledge and showcases how both can be combined to design curricula and assessment measures for DVL. Earlier versions of the DVL-FW have been used to teach DVL to more than 8,500 residential and online students, and results from this effort have helped revise and validate the DVL-FW presented here.