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Related Experiment Videos

Role of multiple resources in predicting time-sharing efficiency: evaluation of three workload models in a

K J Sarno1, C D Wickens

  • 1Institute of Aviation, University of Illinois at Urbana-Champaign, USA.

The International Journal of Aviation Psychology
|January 1, 1995
PubMed
Summary
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This study validated three workload models using a flight simulator. Models accurately predicted workload variance, emphasizing the importance of multiple-resource coding for accurate workload prediction.

Area of Science:

  • Human-Computer Interaction
  • Cognitive Psychology
  • Human Factors Engineering

Background:

  • Workload models are crucial for predicting task performance and system design.
  • Existing models like Time-Line Analysis and Prediction, VACP, and W/INDEX have distinct assumptions.
  • Validating these models is essential for their practical application in complex environments.

Purpose of the Study:

  • To assess the validity of three prominent workload models: Time-Line Analysis and Prediction, VACP, and W/INDEX.
  • To evaluate the predictive accuracy of these models against empirical data from a flight simulation.
  • To identify key features contributing to model fit and compare them to a basic time-line model.

Main Methods:

  • A low-fidelity flight simulation was used with 16 subjects performing tracking, monitoring, and decision tasks.

Related Experiment Videos

  • The decision task featured 16 variations across input modality, processing code, difficulty, and response modality.
  • Tracking performance was analyzed using ANOVA and correlational analysis against workload model predictions.

    • Main Results:

    • Dual-task costs were observed solely in the tracking task.
    • Tracking performance improved with easier concurrent decision tasks and vocal responses.
    • All three workload models effectively predicted between 56% and 84% of the variance in the experimental data.

    Conclusions:

    • Multiple-resource coding is a critical feature for accurate workload modeling.
    • The specific coding features within multiple-resource models require further investigation.
    • Task demand level coding appears less critical for predictive accuracy compared to resource coding.