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Eye Tracking in HCI and Usability Research
Abstract
Eye tracking is a technique whereby an individual’s eye movements are measured so that the researcher knows both where a person is looking at any given time and the sequence in which the person’s eyes are shifting from one location to another. Tracking people’s eye movements can help HCI researchers to understand visual and display-based information processing and the factors that may impact the usability of system interfaces. In this way, eye-movement recordings can provide an objective source of interface-evaluation data that can inform the design of improved interfaces. Eye movements also can be captured and used as control signals to enable people to interact with interfaces directly without the need for mouse or keyboard input, which can be a major advantage for certain populations of users, such as disabled individuals. We begin this article with an overview of eye-tracking technology and progress toward a detailed discussion of the use of eye tracking in HCI and usability research. A key element of this discussion is to provide a practical guide to inform researchers of the various eye-movement measures that can be taken and the way in which these metrics can address questions about system usability. We conclude by considering the future prospects for eye-tracking research in HCI and usability testing.
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“The higher the number of fixations, the more difficult it is to identify the target in the search task and the greater the cognitive load (Poole and Ball, 2006).”
From The impact of usage experience and input modality on trust experience and cognitive load in older adults (2025) · cites this paper as Poole and Ball, 2006
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Intelligent agent transparency in human–agent teaming for multi-UxV management
Mercado, J. E., Rupp, M. A., Chen, J. Y. C., Barnes, M. J., Barber, D., & Procci, K. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815621206 · Cited by 403
“The SMI (SensoMotoric Instruments) Remote Eye-Tracking Device (RED) was used to collect ocular indices to measure visual attention (Hoffman & Subramaniam, 1995) and workload (Poole & Ball, 2006; Figure 1).”
MethodHergeth, S., Lorenz, L., Vilimek, R., & Krems, J. F. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815625744 · Cited by 355
“Even so, eye trackers are sensitive instruments and will not always provide usable data, for example if there are interferences with eye-wear (Poole & Ball, 2006).”
BackgroundSirois, L., Bédard, J., & Bera, P. (2018) · Accounting Horizons · doi:10.2308/acch-52047 · Cited by 323
Multimodal data capabilities for learning: What can multimodal data tell us about learning?
Sharma, K., & Giannakos, M. N. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.12993 · Cited by 281
“For example, gaze data can provide attentional information (Poole & Ball, 2006 ), physiological data can provide information about stress and arousal states of learners (Sharma, Pappas, et al ., 2019 ), and gesture, posture and motion data can tell us about the way learners interact/communicate…”
BackgroundA systematic literature review on the usage of eye-tracking in software engineering
Sharafi, Z., Soh, Z., & Guéhéneuc, Y. (2015) · Information and Software Technology · doi:10.1016/j.infsof.2015.06.008 · Cited by 212
Metadata
- Authors
- Poole, A., & Ball, L. J.
- Affiliations
- Lancaster University (GB)
- ORCID
- Ball, Linden J.
- Venue
- Encyclopedia of Human Computer Interaction
- Publisher
- IGI Global
- Published
- 2006
- Pages
- 211-219
- OpenAlex
- W401941822
- Cited by
- 690
- References
- 0
- Citations by year
- 2026: 34 · 2025: 37 · 2024: 32 · 2023: 43 · 2022: 46 · 2021: 56 · 2020: 66 · 2019: 49 · 2018: 74 · 2017: 47 · 2016: 51 · 2015: 37 · 2014: 42 · 2013: 35 · 2012: 16
- Type
- reference entry
- Language
- en
- Open access
- closed
- Locations
- IGI Global eBooks (publishedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Keywords
- eye tracking, eye movements, usability evaluation, human-computer interaction, eye movement metrics, visual processing, gaze-based interaction, assistive technology for people with disabilities, interface design
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