Keywords: education, visualization software, software agnostic, curriculum design
We propose a three-pronged approach to data visualization education, which we argue does a good job of serving a broad set of institutions (whether in academia or beyond). We outline recommended materials for three different audiences:
* First, a single lecture or short-course, promoting best practices & principles for visual communication. Audience: high-level decision makers, faculty colleagues. Could also be a standalone module for use in e.g. Research Methods courses in the sciences. * Second, a longer course or reading group, for practice in applying those principles---but software-agnostic so that experienced participants can each use their own familiar visualization tools. Audience: graduate students or more-experienced colleagues with their own data to visualize. * Third, an extended course, digging into the details for novices who need more time & guidance in order to learn visualization software and principles at the same time. Audience: undergraduates or less-experienced coworkers ready to learn new tools.
We will provide resources for each level including sample course outlines, learning outcomes, practice assignments, grading rubrics, and suggested readings. This material is based on our experiences designing and teaching courses at all three levels at the US Census Bureau, Carnegie Mellon University, and Colby College.