Challenges and Opportunities for Tool Adoption in Industrial UX Research Collaborations
Daye Kang, Jeffrey M. Rzeszotarski
摘要
UX research practitioners analyze qualitative data to comprehend users' needs and synthesize design implications for software systems. Collaborating with multiple stakeholders is inevitable for these professionals and adds additional pressure to their already laborious data analysis tasks. In this paper, we investigate how these practitioners' multi-stakeholder collaboration affects their data analysis practices. Specifically, we investigate the challenges qualitative UX research (QUXR) practitioners face, limitations of the current qualitative data analysis (QDA) support tools they use, and design implications for future QDA tools to address the limitations. Through semi-structured interviews combined with diagramming activities with thirteen industry QUXR practitioners, we have revealed that collaboration becomes a bigger challenge than data analysis and that it often leads to (1) preferring simple tools despite the QDA specialized tools' beneficial features and (2) wanting to triangulate their work to convince stakeholders. Finally, we have synthesized these results and suggest design implications for QDA support tools.
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