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PRODID:Linklings LLC
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TZID:America/Chicago
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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135133Z
LOCATION:Grand Hall K
DTSTART;TZID=America/Chicago:20251016T171000
DTEND;TZID=America/Chicago:20251016T173000
UID:HFESAM_ASPIRE 2025_sess222_LECT587@linklings.com
SUMMARY:Towards Scalable Research: Comparing Qualitative and Quantitative 
 Data Collection Mechanisms
DESCRIPTION:Dane Morey, Mengyun Li, Mimi Cai, Prerana Walli, Julianna Hreb
 enach, and Michael Rayo (The Ohio State University)\n\nThere is an urgent 
 need for human factors methods which can match the pace and scale of AI de
 velopment. In this study, we compared two data collection mechanisms to pr
 obe nurses’ understanding of an AI-infused patient data display. We collec
 ted responses from two sets of similar questions in alternative formats: (
 1) open-ended free text responses and (2) constrained multi-select respons
 es. We found nurses were significantly more likely to report 11 of 15 resp
 onse categories with the multi-select condition. Additionally, we found nu
 rses with the multi-select condition exhibited significantly different beh
 aviors interacting with the display; however, we found little evidence of 
 differences in task performance. Our findings emphasize that structuring d
 ata collection mechanisms to support quick data processing can induce diff
 erent responses and behaviors that are not directly comparable.\n\nTrack: 
 Cognitive Engineering & Decision Making, Usability and System Evaluation\n
 \nSession Chairs: Sherry Chappell (Federal Aviation Administration (Retire
 d)) and Pratima Saravanan (Oklahoma State University)\n\n
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