Critical Making as Pedagogical Approach to the Data Science Classroom

A data physicalization is a material artifact where data is intentionally encoded. It represents data through physical, tangible forms, such as creating a three-dimensional wooden model of a state's population density by county to enable users to explore and interact with the data in a more intuitive and engaging manner. As a result, data physicalizations keep humans in the loop by engaging their audience and communicating data using tangible representations. While physicalizations can historically be traced back to ancient and premodern examples such as Mesopotamian clay tokens and medieval tally sticks, there are innovative opportunities for instructors to explore the intersection of data science and critical making to convey data. Most importantly, while there are still challenges, introducing students to physicalizations allows them to experience data as a medium, addressing accessibility and multimodal learning styles – particularly kinesthetic and haptic learners. In this interactive session, participants will be introduced to data physicalization as both a form of critical making and a pedagogical tool that can be used to curate, analyze, and interpret data while keeping accessibility in mind. The session will include a brief history of data physicalization, a presentation on data physicalization as alternative pedagogical method for teaching data science, and a hands-on workshop for participants to create examples of physicalizations that can be scaled to their workshops and classrooms.