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Using Eye Tracking to Identify Cognitive Differences: A Brief Literature Review

Authors:

George E. Raptis,

Christos A. Fidas,

Nikolaos M. AvourisAuthors Info & Claims

PCI '16: Proceedings of the 20th Pan-Hellenic Conference on Informatics

Article No.: 21, Pages 1 - 6

https://doi.org/10.1145/3003733.3003762

Published: 10 November 2016 Publication History

Abstract

Being the windows to the soul, eyes reveal information about individuals' feelings, emotions and behaviour, affecting various cognitive tasks, such as focus of attention, spatial cognition and navigation, cognitive load, etc. With the increased use of computer systems, complex information is visualized and communicated through visual interfaces as a mean of information presentation to and processing by the users. However, people differ regarding the way they seek, retrieve, process, comprehend, organize and recall information, based on their individual perceptual characteristics, cognitive skills, abilities and styles. Therefore, the point and the motion of the eye gaze could reveal behavioural patterns related to individual cognitive differences; patterns that are extracted using eye tracking tools which quantify and provide compelling data regarding eye gaze movement. In this paper we review the current literature regarding the effect between the FD-I cognitive style of users in visual exploration and search activities and to correlate these with objective measures gathered through eye-tracking.

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Cited By

Měkota T(2024)Using eye tracking to study reading landscape: a systematic reviewAUC GEOGRAPHICA10.14712/23361980.2024.859:1(120-136)Online publication date: 24-Jun-2024
https://doi.org/10.14712/23361980.2024.8
Specian Junior FLitchfield DSandars JCecilio-Fernandes D(2024)Use of eye tracking in medical educationMedical Teacher10.1080/0142159X.2024.231686346:11(1502-1509)Online publication date: 21-Feb-2024
https://doi.org/10.1080/0142159X.2024.2316863
Steichen B(2024)Computational Methods to Infer Human Factors for Adaptation and Personalization Using Eye TrackingA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_7(183-204)Online publication date: 1-May-2024
https://doi.org/10.1007/978-3-031-55109-3_7
Show More Cited By

Using Eye Tracking to Identify Cognitive Differences: A Brief Literature Review
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
2. Human-centered computing

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cover image ACM Other conferences

PCI '16: Proceedings of the 20th Pan-Hellenic Conference on Informatics

November 2016

449 pages

ISBN:9781450347891

DOI:10.1145/3003733

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Greek Com Soc: Greek Computer Society
TEI: Technological Educational Institution of Athens

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Association for Computing Machinery

New York, NY, United States

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Published: 10 November 2016

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PCI '16

PCI '16: 20th Pan-Hellenic Conference on Informatics

November 10 - 12, 2016

Patras, Greece

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Overall Acceptance Rate 190 of 390 submissions, 49%

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Cited By

Měkota T(2024)Using eye tracking to study reading landscape: a systematic reviewAUC GEOGRAPHICA10.14712/23361980.2024.859:1(120-136)Online publication date: 24-Jun-2024
https://doi.org/10.14712/23361980.2024.8
Specian Junior FLitchfield DSandars JCecilio-Fernandes D(2024)Use of eye tracking in medical educationMedical Teacher10.1080/0142159X.2024.231686346:11(1502-1509)Online publication date: 21-Feb-2024
https://doi.org/10.1080/0142159X.2024.2316863
Steichen B(2024)Computational Methods to Infer Human Factors for Adaptation and Personalization Using Eye TrackingA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_7(183-204)Online publication date: 1-May-2024
https://doi.org/10.1007/978-3-031-55109-3_7
Wang CWu KJiang W(2023)Web-based drawing for students with different learning styles and cognitive abilitiesEducation and Information Technologies10.1007/s10639-022-11542-228:7(9049-9079)Online publication date: 7-Jan-2023
https://doi.org/10.1007/s10639-022-11542-2
Lachaud LTissier GBallenghein U(2023)Mindfulness Is in the Eye of the MachineHuman and Artificial Rationalities10.1007/978-3-031-55245-8_15(223-239)Online publication date: 19-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-55245-8_15
Fang YNi GGao FZhang QNiu MDing Z(2022)Influencing Mechanism of Safety Sign Features on Visual Attention of Construction Workers: A Study Based on Eye-Tracking TechnologyBuildings10.3390/buildings1211188312:11(1883)Online publication date: 4-Nov-2022
https://doi.org/10.3390/buildings12111883
Lian XHong WXu XKimberly KWang Z(2022)The influence of picture book design on visual attention of children with autism: a pilot studyInternational Journal of Developmental Disabilities10.1080/20473869.2022.203359069:6(946-956)Online publication date: 14-Feb-2022
https://doi.org/10.1080/20473869.2022.2033590
Raptis GKatsini C(2021)Analyzing Scanpaths From A Field Dependence-Independence Perspective When Playing A Visual Search GameACM Symposium on Eye Tracking Research and Applications10.1145/3448018.3459655(1-7)Online publication date: 25-May-2021
https://dl.acm.org/doi/10.1145/3448018.3459655
Steichen BFu BNguyen T(2020)Inferring Cognitive Style from Eye Gaze Behavior During Information Visualization UsageProceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3340631.3394881(348-352)Online publication date: 7-Jul-2020
https://dl.acm.org/doi/10.1145/3340631.3394881
Fidas C(2019)Eye Tracking based Cognitive-Centered User ModelsIEEE/WIC/ACM International Conference on Web Intelligence10.1145/3350546.3352563(433-437)Online publication date: 14-Oct-2019
https://dl.acm.org/doi/10.1145/3350546.3352563
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