Cognitive strategies and eye movements for searching hierarchical computer displays

Hornof, Anthony J.; Halverson, Tim

doi:10.1145/642611.642656

Cited by 53 publications

(20 citation statements)

References 9 publications

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“…The experiment was run again by Hornof and Halverson (2003) to collect eye movement data that were used to evaluate the models in more detail. Sixteen people participated in each study.…”

Section: Cvc Taskmentioning

confidence: 99%

“…Previous research suggests that a straightforward way to predict the observed number of fixations in a search task is to assume that two or three objects are processed per fixation (Hornof & Halverson, 2003). For this model, the EPIC visual-perceptual processor availability function was modified so that two or three words were processed per fixation regardless of density.…”

Section: Modeling What Is Perceived During a Fixationmentioning

confidence: 99%

“…Otherwise, the probability of the model correctly perceiving the text is 50%. These probabilities were chosen because they result in an average of two to three items perceived per fixation across both densities, which previous modeling suggests is a good estimate of the number of items processed per fixation (Hornof & Halverson, 2003).…”

Section: Modeling What Is Perceived During a Fixationmentioning

confidence: 99%

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A Computational Model of “Active Vision” for Visual Search in Human–Computer Interaction

Halverson

Hornof

2011

Human–Computer Interaction

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Human visual search plays an important role in many human-computer interaction (HCI) tasks. Better models of visual search are needed not just to predict overall performance outcomes, such as whether people will be able to find the information needed to complete an HCI task, but to understand the many human processes that interact in visual search, which will in turn inform the detailed design of better user interfaces. This article describes a detailed instantiation, in the form of a computational cognitive model, of a comprehensive theory of human visual processing known as ''active vision'' (Findlay & Gilchrist, 2003). The computational model is built using the Executive Process-Interactive Control cognitive architecture. Eye-tracking data from three experiments inform the development and validation of the model. The modeling asks-and at least partially answers-the four questions of active vision: (a) What can be perceived in a fixation? (b) When do the eyes move? (c) Where do the eyes move? (d) What information is integrated between eye movements? Answers include: (a) Items nearer the point of gaze are more likely to be perceived, and the visual features of objects are sometimes misidentified. (b) The eyes move after the fixated visual stimulus has been processed (i.e., has entered working memory). (c) The eyes tend to go to nearby objects. (d) Only the coarse spatial information of what has been fixated is likely maintained between fixations. The model developed to answer these questions has both scientific and practical value in that the model gives Tim Halverson is a cognitive scientist with an interest in human-computer interaction, cognitive modeling, eye movements, and fatigue; he is a Research Computer Scientist in the Applied Neuroscience Branch of the Air Force Research Laboratory. Anthony Hornof is a computer scientist with an interest in human-computer interaction, cognitive modeling, visual search, and eye tracking; he is an Associate Professor in the

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“…The experiment was run again by Hornof and Halverson (2003) to collect eye movement data that were used to evaluate the models in more detail. Sixteen people participated in each study.…”

Section: Cvc Taskmentioning

confidence: 99%

Section: Modeling What Is Perceived During a Fixationmentioning

confidence: 99%

Section: Modeling What Is Perceived During a Fixationmentioning

confidence: 99%

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A Computational Model of “Active Vision” for Visual Search in Human–Computer Interaction

Halverson

Hornof

2011

Human–Computer Interaction

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“…e.g. [4]. To what extent can eyetracking contribute to the measurement of the five "E"s, efficiency, effectiveness, ease of learning, engagement, error tolerance [7]?…”

Section: Commercial Issuesmentioning

confidence: 99%

Getting a measure of satisfaction from eyetracking in practice

Renshaw

Finlay

Webb³

2006

CHI '06 Extended Abstracts on Human Factors in Computing Systems

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Eyetracking is now an almost standard offering from commercial HCI analysts. However, what are the best ways to exploit the strengths and minimise the weaknesses of this technique? This workshop aims to gather individuals who have an interest in using eyetracking for the evaluation and design of digital interfaces such as websites, games, iTV, mobile phones and more. There are two expected outcomes from this workshop. One is to define best practice, suggest answers to continuing areas of doubt and highlight unanswered questions about eyetracking in both the scientific and commercial environment. The other is to explore how best to measure the satisfaction element of the ISO 9241 definition of usability through eye movement analysis especially in the genre of display cited above.Please note interactive eyetracking such as eye typing is not within the focus of this workshop.

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“…Blind users generally use screen readers to convert text and interaction controls on graphical user interfaces into synthetic speech output. Unlike sighted users, who often use non-linear and somewhat noisy approaches towards visual scanning of GUI interfaces (Hornof and Kieras, 1997;Hornof and Halverson, 2003), blind users of screen readers must rely on an inherently serial presentation of items: speech output does not lend itself well towards opportunistic scanning.…”

Section: Introductionmentioning

confidence: 99%

Revisiting breadth vs. depth in menu structures for blind users of screen readers

Hochheiser

Lazar

2010

Interacting with Computers

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a b s t r a c tNumerous studies have investigated task performance times for selection from hierarchical menus, with structures containing many choices at each of a few levels (broad, shallow structures) generally outperforming structures containing fewer choices at each of many levels (narrow, deep structures). To see if these results applied to blind users who rely on screen reader software for computer access, we replicated an earlier published study, using 19 blind screen-reader users. Consistent with earlier studies, broader, shallow hierarchies outperformed narrow, deep hierarchies. Task performance times and hypertext lostness measures were correlated. Although further work will be needed to understand specific determinants of task performance rates, these results support the use of broad, shallow menus for blind as well as sighted users.

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Cognitive strategies and eye movements for searching hierarchical computer displays

Cited by 53 publications

References 9 publications

A Computational Model of “Active Vision” for Visual Search in Human–Computer Interaction

A Computational Model of “Active Vision” for Visual Search in Human–Computer Interaction

Getting a measure of satisfaction from eyetracking in practice

Revisiting breadth vs. depth in menu structures for blind users of screen readers

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