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Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures
Jacob R Kintz1, Neil T Banerjee1, Johnny Y Zhang1
1Smead Department of Aerospace Engineering Sciences, University of Colorado-Boulder, Boulder, Colorado, USA.
Objective:
We use a set of unobtrusive measures to estimate subjectively reported trust, mental workload, and situation awareness (henceforth "TWSA").
Background:
Subjective questionnaires are commonly used to assess human cognitive states. However, they are obtrusive and usually impractical to administer during operations. Measures derived from actions operators take while working (which we call "embedded measures") have been proposed as an unobtrusive way to obtain TWSA estimates. Embedded measures have not been systematically investigated for each of TWSA, which prevents their operational utility.
Methods:
Fifteen participants completed twelve trials of spaceflight-relevant tasks while using a simulated autonomous system. Embedded measures of TWSA were obtained during each trial and participants completed TWSA questionnaires after each trial. Statistical models incorporating our embedded measures were fit with various formulations, interaction effects, and levels of personalization to understand their benefits and improve model accuracy.
Results:
The stepwise algorithm for building statistical models usually included embedded measures, which frequently corresponded to an intuitive increase or decrease in reported TWSA. Embedded measures alone could not accurately capture an operator's cognitive state, but combining the measures with readily observable task information or information about participants' backgrounds enabled the models to achieve good descriptive fit and accurate prediction of TWSA.
Conclusion:
Statistical models leveraging embedded measures of TWSA can be used to accurately estimate responses on subjective questionnaires that measure TWSA.
Application:
Our systematic approach to investigating embedded measures and fitting models allows for cognitive state estimation without disrupting tasks when administering questionnaires would be impractical.
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