Teaching Data Science Students to Sketch Privacy Designs through Heuristics (Extended Technical Report)

April 07, 2025 Β· Declared Dead Β· πŸ› IEEE Symposium on Security and Privacy

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Authors Jinhe Wen, Yingxi Zhao, Wenqian Xu, Yaxing Yao, Haojian Jin arXiv ID 2504.04734 Category cs.HC: Human-Computer Interaction Cross-listed cs.CR, cs.CY Citations 0 Venue IEEE Symposium on Security and Privacy Last Checked 4 months ago
Abstract
Recent studies reveal that experienced data practitioners often draw sketches to facilitate communication around privacy design concepts. However, there is limited understanding of how we can help novice students develop such communication skills. This paper studies methods for lowering novice data science students' barriers to creating high-quality privacy sketches. We first conducted a need-finding study (N=12) to identify barriers students face when sketching privacy designs. We then used a human-centered design approach to guide the method development, culminating in three simple, text-based heuristics. Our user studies with 24 data science students revealed that simply presenting three heuristics to the participants at the beginning of the study can enhance the coverage of privacy-related design decisions in sketches, reduce the mental effort required for creating sketches, and improve the readability of the final sketches.
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