Presentation
Towards Scalable Research: Comparing Qualitative and Quantitative Data Collection Mechanisms
DescriptionThere is an urgent need for human factors methods which can match the pace and scale of AI development. In this study, we compared two data collection mechanisms to probe nurses’ understanding of an AI-infused patient data display. We collected responses from two sets of similar questions in alternative formats: (1) open-ended free text responses and (2) constrained multi-select responses. We found nurses were significantly more likely to report 11 of 15 response categories with the multi-select condition. Additionally, we found nurses with the multi-select condition exhibited significantly different behaviors interacting with the display; however, we found little evidence of differences in task performance. Our findings emphasize that structuring data collection mechanisms to support quick data processing can induce different responses and behaviors that are not directly comparable.
Event Type
Industry/Practitioner Content
Lecture
TimeThursday, October 16th5:10pm - 5:30pm CDT
LocationGrand Hall K
Cognitive Engineering & Decision Making
Usability and System Evaluation
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