Improved Measures of Data Visualization Literacy to Advance Research and Assessment in STEM Education

Stanford University, Stanford CA

Investigators

Abstract

Data visualization literacy plays a pivotal role in effectively communicating patterns in quantitative data, making it a cornerstone of STEM education. However, the landscape of test-based measures for assessing these skills is fragmented, without clear agreement on how to measure the key components of data visualization literacy. Furthermore, there might also be important aspects of data visualization literacy that are not well captured by existing measures. This project seeks to overcome these limitations by thoroughly characterizing existing measures and leveraging the resulting insights to develop improved and unified measures of data visualization literacy. The research plan is organized into three objectives. The first will focus on conducting controlled studies to determine the internal reliability and convergent validity of existing measures of data visualization literacy in demographically diverse samples. The second objective will focus on the development of reproducible procedures for generating new measures that span the full spectrum of tasks and data visualizations used in existing measures, while also overcoming some of their most important limitations, including uneven estimation precision across different components of data visualization literacy. The third objective will administer multiple variants of newly developed measures to multiple diverse samples, providing a strong test of their reliability. Taken together, these activities will generate a suite of well validated and comprehensive measures for assessing data visualization literacy skills. In the future, these new measures can then be used to understand how well core data literacy skills are being learned in real-world educational settings. This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. 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.