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


Lanini-Maggi, Sara; Ruginski, Ian T; Shipley, Thomas F; Hurter, Christophe; Duchowski, Andrew T; Briesemeister, Benny B; Lee, Jihyun; Fabrikant, Sara I (2021). Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task. Computers in Human Behavior Reports, 4:100127.

Abstract

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.

Abstract

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:1 August 2021
Deposited On:06 Aug 2021 08:07
Last Modified:06 Aug 2021 08:07
Publisher:Elsevier
ISSN:2451-9588
OA Status:Green
Publisher DOI:https://doi.org/10.1016/j.chbr.2021.100127

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