Fixing Inclusivity Bugs for Information Processing Styles and Learning Styles
May 07, 2019 Β· Declared Dead Β· π arXiv.org
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Authors
Zoe Steine-Hanson, Claudia Hilderbrand, Lara Letaw, Jillian Emard, Christopher Perdriau, Christopher Mendez, Margaret Burnett, Anita Sarma
arXiv ID
1905.02813
Category
cs.HC: Human-Computer Interaction
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Most software systems today do not support cognitive diversity. Further, because of differences in problem-solving styles that cluster by gender, software that poorly supports cognitive diversity can also embed gender biases. To help software professionals fix gender bias "bugs" related to people's problem-solving styles for information processing and learning of new software we collected inclusivity fixes from three sources. The first two are empirical studies we conducted: a heuristics-driven user study and a field research industry study. The third is data that we obtained about a before/after user study of inclusivity bugs. The resulting seven potential inclusivity fixes show how to debug software to be more inclusive for diverse problem-solving styles.
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