Input Physicalization in Practice: An Instructional Walkthrough with Visualization Novices

Abstract:

We conduct an instructional walkthrough with undergraduate students who have limited to no visualization knowledge and create three physicalizations with personal data input. While physicalization is widely recognized as a tangible, intuitive, and engaging form of data representation, its design and construction remain challenging, especially for novices who lack basic visualization knowledge. To explore these challenges in practice, we conducted an instructional walkthrough with undergraduate students who have limited to no visualization expertise. A group of students first elicited possible personal data, which was then filtered and categorized under supervision. Next, one lead student discussed with the supervisors to determine the reasonable data items to design with, as well as the possible data input methods. After which, the student individually modeled and fabricated the physicalizations that have corresponding data input mechanisms, and used these physicalizations to complete a period of data input. Our walkthrough revealed insights into input physicalization in connection with visualization novices and education, as well as the research gaps between observed novice challenges with input visualization. Supplemental materials and demo videos are available at osf.io/8quv4/.