Modeling the Cognitive Task Load and Performance of Naval Operators

  • Mark A. Neerincx
  • Stefan Kennedie
  • Marc Grootjen
  • Franc Grootjen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5638)

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.

Keywords

mental load emotion Bayesian networks cognitive engineering Defense and Space operations 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Mark A. Neerincx
    • 1
    • 2
  • Stefan Kennedie
    • 1
    • 5
  • Marc Grootjen
    • 2
    • 3
  • Franc Grootjen
    • 4
    • 5
  1. 1.TNO Human FactorsSoesterbergThe Netherlands
  2. 2.Delft University of TechnologyDelftThe Netherlands
  3. 3.Defense Materiel Organization, Directorate Materiel Royal Netherlands NavyThe HagueThe Netherlands
  4. 4.Donders Centre for CognitionRadboud University NijmegenNijmegenThe Netherlands
  5. 5.Radboud University NijmegenThe Netherlands

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