research-article

Recurrence quantification analysis reveals eye-movement behavior differences between experts and novices

Authors:

Preethi Vaidyanathan,

Jeff Pelz,

Cecilia Alm,

Pengcheng Shi,

Anne HaakeAuthors Info & Claims

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

Pages 303 - 306

https://doi.org/10.1145/2578153.2578207

Published: 26 March 2014 Publication History

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Abstract

Understanding and characterizing perceptual expertise is a major bottleneck in developing intelligent systems. In knowledge-rich domains such as dermatology, perceptual expertise influences the diagnostic inferences made based on the visual input. This study uses eye movement data from 12 dermatology experts and 12 undergraduate novices while they inspected 34 dermatological images. This work investigates the differences in global and local temporal fixation patterns between the two groups using recurrence quantification analysis (RQA). The RQA measures reveal significant differences in both global and local temporal patterns between the two groups. Results show that experts tended to refixate previously inspected areas less often than did novices, and their refixations were more widely separated in time. Experts were also less likely to follow extended scan paths repeatedly than were novices. These results suggest the potential value of RQA measures in characterizing perceptual expertise. We also discuss potential use of the RQA method in understanding the interactions between experts' visual and linguistic behavior.

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Cited By

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Niehorster DNyström MHessels RAndersson RBenjamins JHansen DHooge I(2025)The fundamentals of eye tracking part 4: Tools for conducting an eye tracking studyBehavior Research Methods10.3758/s13428-024-02529-757:1Online publication date: 6-Jan-2025
https://doi.org/10.3758/s13428-024-02529-7
Eloy LSpencer CDoherty EHirshfield L(2023)Capturing the Dynamics of Trust and Team Processes in Human-Human-Agent Teams via Multidimensional Neural Recurrence AnalysesProceedings of the ACM on Human-Computer Interaction10.1145/35795987:CSCW1(1-23)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579598
Guglielmo GBlom PKlincewicz MCule BSpronck P(2022)Face in the Game: Using Facial Action Units to Track Expertise in Competitive Video Game Play2022 IEEE Conference on Games (CoG)10.1109/CoG51982.2022.9893599(112-118)Online publication date: 21-Aug-2022
https://doi.org/10.1109/CoG51982.2022.9893599
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Index Terms

Recurrence quantification analysis reveals eye-movement behavior differences between experts and novices
1. Computing methodologies
  1. Computer graphics
    1. Graphics systems and interfaces
      1. Perception
2. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

March 2014

394 pages

ISBN:9781450327510

DOI:10.1145/2578153

Conference Chairs:
Pernilla Qvarfordt
FX Palo Alto Laboratory
,
Dan Witzner Hansen
IT University, Denmark

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 26 March 2014

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ETRA '14: Eye Tracking Research and Applications

March 26 - 28, 2014

Florida, Safety Harbor

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Overall Acceptance Rate 69 of 137 submissions, 50%

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2025 Symposium on Eye Tracking Research and Applications

May 26 - 29, 2025

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Niehorster DNyström MHessels RAndersson RBenjamins JHansen DHooge I(2025)The fundamentals of eye tracking part 4: Tools for conducting an eye tracking studyBehavior Research Methods10.3758/s13428-024-02529-757:1Online publication date: 6-Jan-2025
https://doi.org/10.3758/s13428-024-02529-7
Eloy LSpencer CDoherty EHirshfield L(2023)Capturing the Dynamics of Trust and Team Processes in Human-Human-Agent Teams via Multidimensional Neural Recurrence AnalysesProceedings of the ACM on Human-Computer Interaction10.1145/35795987:CSCW1(1-23)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579598
Guglielmo GBlom PKlincewicz MCule BSpronck P(2022)Face in the Game: Using Facial Action Units to Track Expertise in Competitive Video Game Play2022 IEEE Conference on Games (CoG)10.1109/CoG51982.2022.9893599(112-118)Online publication date: 21-Aug-2022
https://doi.org/10.1109/CoG51982.2022.9893599
Lanata ASebastiani LDi Gruttola FDi Modica SScilingo EGreco A(2020)Nonlinear Analysis of Eye-Tracking Information for Motor Imagery AssessmentsFrontiers in Neuroscience10.3389/fnins.2019.0143113Online publication date: 15-Jan-2020
https://doi.org/10.3389/fnins.2019.01431
Hofmaenner DKlinzing SBrandi GHess SLohmeyer QEnthofer KSchuepbach RBuehler P(2020)The doctor's point of view: eye-tracking as an investigative tool in the extubation process in intensive care units. A pilot studyMinerva Anestesiologica10.23736/S0375-9393.20.14468-786:11Online publication date: Nov-2020
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Danvers ASbarra DMehl M(2020)Understanding Personality through Patterns of Daily Socializing: Applying Recurrence Quantification Analysis to Naturalistically Observed Intensive Longitudinal Social Interaction DataEuropean Journal of Personality10.1002/per.228234:5(777-793)Online publication date: 1-Sep-2020
https://doi.org/10.1002/per.2282
Gurtner LBischof WMast F(2019)Recurrence quantification analysis of eye movements during mental imageryJournal of Vision10.1167/19.1.1719:1(17)Online publication date: 30-Jan-2019
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Eloy LE.B. Stewart AJean Amon MReinhardt CMichaels ASun CShute VDuran ND'Mello S(2019)Modeling Team-level Multimodal Dynamics during Multiparty Collaboration2019 International Conference on Multimodal Interaction10.1145/3340555.3353748(244-258)Online publication date: 14-Oct-2019
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Vrzakova HAmon MStewart AD'Mello SBrewster SFitzpatrick GCox AKostakos V(2019)Dynamics of Visual Attention in Multiparty Collaborative Problem Solving using Multidimensional Recurrence Quantification AnalysisProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300572(1-14)Online publication date: 2-May-2019
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Amon MVrzakova HD'Mello S(2019)Beyond Dyadic Coordination: Multimodal Behavioral Irregularity in Triads Predicts Facets of Collaborative Problem SolvingCognitive Science10.1111/cogs.1278743:10Online publication date: 6-Oct-2019
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Determining Differences in Reading Behavior Between Experts and Novices by Investigating Eye Movement on Source Code Constructs During a Bug Fixing Task

Cognitive analysis of experts' and novices' concept mapping processes

Recurrence Quantification Analysis of Eye Gaze Dynamics During Team Collaboration

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