Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task

Computers in Human Behavior Reports

Ian T. Ruginski¹  Sara I. Fabrikant²  Benny B. Briesemeister³  Christophe Hurter⁴  Andrew T. Duchowski⁵  Jihyun Lee⁶  Sara Lanini-Maggi⁷  Thomas F. Shipley⁷ 

[1] Corresponding author.;Neurospective GmbH, Berlin, 13589, Germany;Clemson University, School of Computing, Clemson, SC, 29634, USA;Department of Psychology, RISC lab (Research in Spatial Cognition Lab), Temple University, Philadelphia, PA, 19122, USA;ENAC, Ecole Nationale de l’Aviation Civile, University of Toulouse, Toulouse, 31055, France;Free University, Department of Psychology, Berlin, 14195, Germany;University of Zurich, Department of Geography / Digital Society Initiative, Zurich, 8057, Switzerland;

关键词: Visual search entropy;    Eye tracking;    Electroencephalography;    Air traffic control;    Animation;    Cross-validation;   

DOI  :  

来源: DOAJ

【 摘 要 】

Behavioral performance metrics employed to assess the usability of visual displays are increasingly coupled with eye tracking measures to provide additional insights into the decision-making processes supported by visual displays. Eye tracking metrics can be coupled with users' neural data to investigate how human cognition interplays with emotions during visuo-spatial tasks. To contribute to these efforts, we present results of a study in a realistic air traffic control (ATC) setting with animated ATC displays, where ATC experts and novices were presented with an aircraft movement detection task. We find that higher stationary gaze entropy – which indicates a larger spatial distribution of visual gaze on the display – and expertise result in better response accuracy, and that stationary entropy positively predicts response time even after controlling for animation type and expertise. As a secondary contribution, we found that a single component comprised of engagement, measured by EEG and self-reported judgments, spatial abilities, and gaze entropy predicts task accuracy, but not completion time. We also provide MATLAB open source code for calculating the EEG measures utilized in the study. Our findings suggest designing spatial information displays that adapt their content according to users’ affective and cognitive states, especially for emotionally laden usage contexts.

【 授权许可】

Unknown