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

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 i...

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Autores principales:	Sara Lanini-Maggi, Ian T. Ruginski, Thomas F. Shipley, Christophe Hurter, Andrew T. Duchowski, Benny B. Briesemeister, Jihyun Lee, Sara I. Fabrikant
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Visual search entropy Eye tracking Electroencephalography Air traffic control Animation Cross-validation Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/d716ff7a8809456facdbe2241a6b3be5
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id	oai:doaj.org-article:d716ff7a8809456facdbe2241a6b3be5
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spelling	oai:doaj.org-article:d716ff7a8809456facdbe2241a6b3be52021-12-01T05:04:36ZAssessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task2451-958810.1016/j.chbr.2021.100127https://doaj.org/article/d716ff7a8809456facdbe2241a6b3be52021-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2451958821000750https://doaj.org/toc/2451-9588Behavioral 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.Sara Lanini-MaggiIan T. RuginskiThomas F. ShipleyChristophe HurterAndrew T. DuchowskiBenny B. BriesemeisterJihyun LeeSara I. FabrikantElsevierarticleVisual search entropyEye trackingElectroencephalographyAir traffic controlAnimationCross-validationElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 4, Iss , Pp 100127- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Visual search entropy Eye tracking Electroencephalography Air traffic control Animation Cross-validation Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Visual search entropy Eye tracking Electroencephalography Air traffic control Animation Cross-validation Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Sara Lanini-Maggi Ian T. Ruginski Thomas F. Shipley Christophe Hurter Andrew T. Duchowski Benny B. Briesemeister Jihyun Lee Sara I. Fabrikant Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
description	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.
format	article
author	Sara Lanini-Maggi Ian T. Ruginski Thomas F. Shipley Christophe Hurter Andrew T. Duchowski Benny B. Briesemeister Jihyun Lee Sara I. Fabrikant
author_facet	Sara Lanini-Maggi Ian T. Ruginski Thomas F. Shipley Christophe Hurter Andrew T. Duchowski Benny B. Briesemeister Jihyun Lee Sara I. Fabrikant
author_sort	Sara Lanini-Maggi
title	Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
title_short	Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
title_full	Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
title_fullStr	Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
title_full_unstemmed	Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
title_sort	assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/d716ff7a8809456facdbe2241a6b3be5
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Assessing how visual search entropy and engagement predict performance in a multiple-objects tracking air traffic control task

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