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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20251016T135141Z
LOCATION:Grand A
DTSTART;TZID=America/Chicago:20251015T115000
DTEND;TZID=America/Chicago:20251015T121000
UID:HFESAM_ASPIRE 2025_sess218_LECT178@linklings.com
SUMMARY:The Role of Task Load for the Use of Adaptable Automation in Dynam
 ic Scenarios
DESCRIPTION:Linda Onnasch, Viktoria Feyerherd, and Tobias Rieger (Technisc
 he Universität Berlin) and Eileen Roesler (George Mason University)\n\nAda
 ptable Automation (AA) offers flexibility in task allocation between human
 s and automation, with humans retaining full control in the allocation dec
 ision. However, previous studies demonstrate that humans rarely utilize th
 is flexibility. This might be associated with stable task load in these st
 udies. Accordingly, the current study examined the impact of task load on 
 AA usage and advantages over static automation with 120 participants worki
 ng on a simulated traffic navigation task.\nThe study used a mixed design 
 with automation as between-subject factor and task load as within-subject 
 factor. Automation was either realized as Decision Automation (DA, high au
 tomation degree), Information Automation (IA, low automation degree) or AA
  (comprising two modes, DA and IA), task load varied between high and low.
  Regardless of task load, the AA group preferred the high automation mode.
  Perceived autonomy was higher in the AA than in the DA group. Workload an
 d performance were comparable to DA and superior to IA support. Perceived 
 involvement was smallest in the AA group and highest in the IA group. \nFi
 ndings point to the potential of AA to combine benefits of high automation
  degrees - such as reduced workload - with greater perceived autonomy typi
 cally associated with lower automation degrees.\n\nTrack: Cognitive Engine
 ering & Decision Making\n\nSession Chairs: Srijani Mukherjee (Member), Ale
 xandra Watral (Mayo Clinic), and Jin Yong Kim (University of Michigan)\n\n
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