Design study 'lite' methodology: Expediting design studies and enabling the synergy of visualization pedagogy and social good

An image showing the different stages of the projects completed by the students using Design Study 'Lite' Methodology. Task abstractions, ideation process low-fidelity sketches, and final visualizations are shown from left to right.
The image presents examples of how students implemented the Design Study 'Lite' Methodology. Task abstractions, ideation process low-fidelity sketches, and final visualizations are shown in the piles from left to right, respectively
Abstract
Design studies are frequently used to conduct problem-driven visualization research by working with real-world domain experts. In visualization pedagogy, design studies are often introduced but rarely practiced due to their large time requirements. This limits students to a classroom curriculum, often involving projects that may not have implications beyond the classroom. Thus we present the Design Study 'Lite' Methodology, a novel framework for implementing design studies with novice students in 14 weeks. We utilized the Design Study 'Lite' Methodology in conjunction with Service-Learning to teach five Data Visualization courses and demonstrate that it benefits not only the students but also the community through service to non-profit partners. In this paper, we provide a detailed breakdown of the methodology and how Service-Learning can be incorporated with it. We also include an extensive reflection on the methodology and provide recommendations for future applications of the framework for teaching visualization courses and research.
Materials
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Authors
Prasanth Murali
Lisa Roe
Becca Berkey
Citation
Thumbnail image for publication titled: Design study 'lite' methodology: Expediting design studies and enabling the synergy of visualization pedagogy and social good
Design study 'lite' methodology: Expediting design studies and enabling the synergy of visualization pedagogy and social good

Uzma Haque Syeda, Prasanth Murali, Lisa Roe, Becca Berkey, and Michelle A. Borkin. In Proc. CHI Conference on Human Factors in Computing Systems—CHI. 2020. DOI: 10.1145/3313831.3376829

PDF | Preprint | DOI | Homepage | Supplement | Video Preview | Video Presentation | Multiple Views Blog | BibTeX | CHI 2020 Best Paper Award!


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