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PRODID:Linklings LLC
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TZID:America/Phoenix
X-LIC-LOCATION:America/Phoenix
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DTSTART:19700101T000000
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BEGIN:VEVENT
DTSTAMP:20241014T203101Z
LOCATION:FLW Salon B
DTSTART;TZID=America/Phoenix:20240910T100500
DTEND;TZID=America/Phoenix:20240910T102500
UID:HFESAM_ASPIRE - Presented by HFES_sess121_LECT361@linklings.com
SUMMARY:Verification and Validation of Cognitive Workload Models for Adapt
 ive Automation Tasks
DESCRIPTION:Lecture\n\nCharles Rowan (Naval Postgraduate School, United St
 ates Army)\n\nTechnological advances that seek to address future operation
 al challenges abound. While advanced capabilities are being developed, the
 re is an important space for human design considerations, including cognit
 ive workload. One proposed solution to improve cognitive workload manageme
 nt is adaptive automation (AA). This research used a novel, model-based ap
 proach to assess the impacts of AA on cognitive workload. This assessment 
 modeled the tasks in NASA’s Multi-attribute Task Battery-II (MATB-II) usin
 g the Improved Performance Research Integration Tool (IMPRINT). The effort
  sought to investigate the relationship of cognitive workload, situation a
 wareness, and performance through three human-in-the-loop studies with 120
  participants using MATB-II. The research also attempted to validate cogni
 tive workload models from IMPRINT. The IMPRINT models were representative 
 of the MATB tasks with statistically significant differences between workl
 oad conditions, which mirrored the models' predictions. The results demons
 trated that AA system task models can be developed using IMPRINT to provid
 e design recommendations.\n\nTrack: Human Performance Modeling\n\nSession 
 Chair: Na Du (University of Pittsburgh)
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