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PRODID:Linklings LLC
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TZID:America/Phoenix
X-LIC-LOCATION:America/Phoenix
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TZOFFSETFROM:-0700
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DTSTART:19700101T000000
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BEGIN:VEVENT
DTSTAMP:20241014T203102Z
LOCATION:McArthur Ballroom
DTSTART;TZID=America/Phoenix:20240912T173000
DTEND;TZID=America/Phoenix:20240912T183000
UID:HFESAM_ASPIRE - Presented by HFES_sess108_POS329@linklings.com
SUMMARY:62. Quantifying Trust Evolution Through Predictability of Complian
 ce Behavior: A Dynamical Systems Perspective
DESCRIPTION:Poster\n\nMatthew Peel (Arizona State University)\n\nRecurrenc
 e quantification analysis (RQA) is a nonlinear technique for modeling dyna
 mic patterns in complex systems (Riley & Van Orden, 2005). The application
  of RQA spans many fields, but notably, has been used to analyze communica
 tion patterns and psychological data to understand team behaviors and soci
 al dynamics, such as coordination, cooperation, and trust (Mitkidis et al.
 , 2015; Tolston et al., 2018; Grimm et al., 2018; Demir et al., 2021). Des
 pite advancements in the application of RQA for understanding human automa
 tion team interactions, the potential of RQA to dynamically characterize t
 rust measures remains largely unexplored (Landfair et al., 2021). These ma
 y reveal novel insight into how trust changes in time and across context. 
 In this paper we address this gap in application by investigating complian
 ce decisions over time to quantify the predictability of trust’s nonlinear
  development in dynamic HAT interactions.\n\nTrack: Aging, Augmented Cogni
 tion, Children's Issues, Communications, Cybersecurity, Education, Environ
 mental Design, General Sessions, Human AI Robot Teaming (AI), Macroergonom
 ics, Occupational Ergonomics, Student Forum, Surface Transportation, Susta
 inability, System Development
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