Modeling the Cognitive Task Load and Performance of Naval Operators

Authors:
Mark A. Neerincx;Stefan Kennedie;Marc Grootjen;Franc Grootjen
Affiliations:
TNO Human Factors, Soesterberg, The Netherlands 3769 ZG and Delft University of Technology, Delft, The Netherlands 2628 GA;TNO Human Factors, Soesterberg, The Netherlands 3769 ZG and Radboud University Nijmegen, The Netherlands;Delft University of Technology, Delft, The Netherlands 2628 GA and Defense Materiel Organization, Directorate Materiel Royal Netherlands Navy, The Hague, The Netherlands 2500 ES;Donders Centre for Cognition, Radboud University Nijmegen, Nijmegen, The Netherlands 6500 HE and Radboud University Nijmegen, The Netherlands
Venue:
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
Year:
2009

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Abstract

Operators on naval ships have to act in dynamic, critical and high-demand task environments. For these environments, a cognitive task load (CTL) model has been proposed as foundation of three operator support functions: adaptive task allocation, cognitive aids and resource feedback. This paper presents the construction of such a model as a Bayesian network with probability relationships between CTL and performance. The network is trained and tested with two datasets: operator performance with an adaptive user interface in a lab-setting and operator performance on a high-tech sailing ship. The "Naïve Bayesian network" tuned out to be the best choice, providing performance estimations with 86% and 74% accuracy for respectively the lab and ship data. Overall, the resulting model nicely generalizes over the two datasets. It will be used to estimate operator performance under momentary CTL-conditions, and to set the thresholds of the load-mitigation strategies for the three support functions.