Proceedings of the Annual Meeting of the Cognitive Science Society

Measuring cognitive workload is a persistent challenge in cog-nitive science. Cognitive architectures may offer a prin-cipledway to measure, define, and understand workload and its be-havioral and physiological consequences in terms ofunder-lying cognitive dynamics. Previous research has shown thatmodel-based workload relates to subjective workloadjudg-ments in simple tasks. Our goal was to further validate model-based workload measurement with known physiolog-ical work-load indicators in a complex task characterized by varying de-grees of workload levels. Participants completedan unmannedvehicle management task while their physiology was recorded.Correlations between model-based workloadand physiologi-cal metrics generally trended in the predicted direction, andthe engagement index showed the strongest andmost consis-tent relationship to model workload. The results provide pre-liminary validation for model-based workloadmeasurement.