research-article

Measuring Cognitive Load using Eye Tracking Technology in Visual Computing

Authors:

Johannes Zagermann,

Harald ReitererAuthors Info & Claims

BELIV '16: Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization

Pages 78 - 85

https://doi.org/10.1145/2993901.2993908

Published: 24 October 2016 Publication History

Abstract

In this position paper we encourage the use of eye tracking measurements to investigate users' cognitive load while interacting with a system. We start with an overview of how eye movements can be interpreted to provide insight about cognitive processes and present a descriptive model representing the relations of eye movements and cognitive load. Then, we discuss how specific characteristics of human-computer interaction (HCI) interfere with the model and impede the application of eye tracking data to measure cognitive load in visual computing. As a result, we present a refined model, embedding the characteristics of HCI into the relation of eye tracking data and cognitive load. Based on this, we argue that eye tracking should be considered as a valuable instrument to analyze cognitive processes in visual computing and suggest future research directions to tackle outstanding issues.

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Cited By

Ahmadi MMichalka SNajafabadi MWünsche BBillinghurst M(2024)EEG, Pupil Dilations, and Other Physiological Measures of Working Memory Load in the Sternberg TaskMultimodal Technologies and Interaction10.3390/mti80400348:4(34)Online publication date: 19-Apr-2024
https://doi.org/10.3390/mti8040034
Shoshina IKovalenko SKuznetsov VBrak IKashevnik A(2024)Related work analysis for determination of fatigue state based on eye movements monitoringФизиология человека10.31857/S013116462403007450:3Online publication date: 16-Sep-2024
https://doi.org/10.31857/S0131164624030074
Ling SZhang YDu N(2024)More Is Not Always Better: Impacts of AI-Generated Confidence and Explanations in Human–Automation InteractionHuman Factors: The Journal of the Human Factors and Ergonomics Society10.1177/00187208241234810Online publication date: 4-Mar-2024
https://doi.org/10.1177/00187208241234810
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Index Terms

Measuring Cognitive Load using Eye Tracking Technology in Visual Computing
1. Human-centered computing
  1. Human computer interaction (HCI)

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BELIV '16: Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization

October 2016

177 pages

ISBN:9781450348188

DOI:10.1145/2993901

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]

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INRIA: INRIA Rhône-Alpes

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Publication History

Published: 24 October 2016

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Deutsche Forschungsgemeinschaft

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BELIV '16

BELIV '16: Novel Evaluation Methods For Visualization

October 24, 2016

MD, Baltimore, USA

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Overall Acceptance Rate 45 of 64 submissions, 70%

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Cited By

Ahmadi MMichalka SNajafabadi MWünsche BBillinghurst M(2024)EEG, Pupil Dilations, and Other Physiological Measures of Working Memory Load in the Sternberg TaskMultimodal Technologies and Interaction10.3390/mti80400348:4(34)Online publication date: 19-Apr-2024
https://doi.org/10.3390/mti8040034
Shoshina IKovalenko SKuznetsov VBrak IKashevnik A(2024)Related work analysis for determination of fatigue state based on eye movements monitoringФизиология человека10.31857/S013116462403007450:3Online publication date: 16-Sep-2024
https://doi.org/10.31857/S0131164624030074
Ling SZhang YDu N(2024)More Is Not Always Better: Impacts of AI-Generated Confidence and Explanations in Human–Automation InteractionHuman Factors: The Journal of the Human Factors and Ergonomics Society10.1177/00187208241234810Online publication date: 4-Mar-2024
https://doi.org/10.1177/00187208241234810
Mazza CCeccato ICannito LMonaro MRicci EBartolini ECardinale ADi Crosta ACardaioli MLa Malva PColasanti MTambelli RGiromini LPalumbo RPalumbo RDi Domenico ARoma P(2024)A Step Forward in Identifying Socially Desirable Respondents: An Integrated Machine Learning Model Considering T‐Scores, Response Time, Kinematic Indicators, and Eye MovementsHuman Behavior and Emerging Technologies10.1155/2024/72670302024:1Online publication date: 11-Oct-2024
https://doi.org/10.1155/2024/7267030
Mottok JHauser FGrabinger LEzer TEngl F(2024)An Educational Perspective on Eye Tracking in Engineering SciencesProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653945(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653945
Thorgeirsson SZhang CWeidmann TWeidmann KSu Z(2024)An Electroencephalography Study on Cognitive Load in Visual and Textual ProgrammingProceedings of the 2024 ACM Conference on International Computing Education Research - Volume 110.1145/3632620.3671124(280-292)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3632620.3671124
Thorgeirsson SWeidmann TWeidmann KSu ZStephenson BStone JBattestilli LRebelsky SShoop L(2024)Comparing Cognitive Load Among Undergraduate Students Programming in Python and the Visual Language AlgotProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630808(1328-1334)Online publication date: 7-Mar-2024
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Murakami TFujita KHara KTakashima KKitamura Y(2024)SwapVid: Integrating Video Viewing and Document Exploration with Direct ManipulationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642515(1-13)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642515
Enge KElmquist ECaiola VRönnberg NRind AIber MLenzi SLan FHöldrich RAigner W(2024)Open Your Ears and Take a Look: A State‐of‐the‐Art Report on the Integration of Sonification and VisualizationComputer Graphics Forum10.1111/cgf.1511443:3Online publication date: 10-Jun-2024
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Tang NChen MNing ZBansal AHuang YMcMillan CLi T(2024)Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking2024 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)10.1109/VL/HCC60511.2024.00015(40-46)Online publication date: 2-Sep-2024
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