Cognitive Strategies for the Visual Search of Hierarchical Computer Displays

Hornof, Anthony J.

doi:10.1207/s15327051hci1903_1

Cited by 44 publications

(47 citation statements)

References 37 publications

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“…There are many cognitive models of visual search that may one day converge to form a solid basis for the theory of visual search in HCI [1,4,12]. While these models are very useful, many such models are designed to explain the effects of particular visual structures or salient features.…”

Section: Introductionmentioning

confidence: 99%

A minimal model for predicting visual search in human-computer interaction

Halverson

Hornof

2007

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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Visual search is an important part of human-computer interaction. It is critical that we build theory about how people visually search displays in order to better support the users' visual capabilities and limitations in everyday tasks. One way of building such theory is through computational cognitive modeling. The ultimate promise for cognitive modeling in HCI it to provide the science base needed for predictive interface analysis tools. This paper discusses computational cognitive modeling of the perceptual, strategic, and oculomotor processes people used in a visual search task. This work refines and rounds out previously reported cognitive modeling and eye tracking analysis. A revised "minimal model" of visual search is presented that explains a variety of eye movement data better than the original model. The revised model uses a parsimonious strategy that is not tied to a particular visual structure or feature beyond the location of objects. Three characteristics of the minimal strategy are discussed in detail.

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Section: Introductionmentioning

confidence: 99%

A minimal model for predicting visual search in human-computer interaction

Halverson

Hornof

2007

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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“…Fixations as revealed by eye tracking studies could be determined by image salience and goal-directed attention [10,11]; however, objects that are actively processed by users may not be the same as those that are fixated. Therefore we investigate the link between fixations, users' perceived attention to objects of interest, their overall preference and memory.…”

Section: Introductionmentioning

confidence: 99%

Investigating User Attention and Interest in Websites

Sutcliffe

Namoun

2007

Lecture Notes in Computer Science

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Abstract. Users' attention was investigated by eye tracking, combined with reported rating of areas of interest, and free recall memory of six operational websites. The sites differed in the pattern of fixations recorded depending on their layout structure. Fixation durations and areas of interest were generally correlated but exceptions were present in both directions. The sites which were rated more attractive overall had an open layout and high density fixations on animations. The sites which were preferred overall had column layout, and content with brand seemed to be the more important determinants for preference. Fixation densities were closely related to reported user interest for 4/6 sites but not for two e-commerce sites. Reported attention, positive memory and overall preference were weakly related.

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“…For example, in the case of the clustered and linear with categories interfaces, participants relied on the labels which accompanied each cluster or category of metadata elements in order to decide whether a group included useful information for relevance judgment. This finding aligns with the systematic visual search process according to which the user first inspects the labels of each group and then selects the target label in order to view its contents (Hornof, 2004).…”

Section: Structure Of Metadata Elementsmentioning

confidence: 92%

Design factors affecting relevance judgment behaviour in the context of metadata surrogates

Balatsoukas

O’Brien

Morris

2010

Journal of Information Science

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For the full text of this licence, please go to: http://creativecommons.org/licenses/by-nc-nd/2.5/ Design factors affecting user interaction and relevance judgment behaviour with metadata surrogates: the case of structure, highlighting and quantity of information AbstractThis paper reports on the findings of a user study which investigated the effects of structure, highlighting and quantity of information on university students' interaction with metadata surrogates of learning object repositories (LORs) during the relevance judgment process. The literature review revealed a lack of studies investigating how metadata surrogates should be designed to meet users' needs and improve the effectiveness of relevance judgment. In order to address this issue, different versions of a prototype system, called META-LOR 2, were developed and evaluated in terms of the time needed for users to find relevant information, the accuracy of their relevance judgments and their satisfaction. To evaluate the prototype, a user study was conducted where test subjects were asked to complete a set of tasks and fill in a satisfaction questionnaire. The findings showed that participants performed better and were more satisfied with those versions of the prototype which highlighted metadata elements that included the query terms, used clusters or categories to organize metadata elements in the surrogates and included metadata elements which were relevant to the query or task at hand. Participants performed less efficiently and were less satisfied with metadata surrogates which lacked the use of a clear structure, did not highlight the query terms and contained a large number of metadata elements. It is anticipated that the findings of this research will enhance understanding of users' interaction with metadata surrogates during the relevance judgment process and improve the design of the search result interfaces of educational information retrieval systems, such as LORs.

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Cognitive Strategies for the Visual Search of Hierarchical Computer Displays

Cited by 44 publications

References 37 publications

A minimal model for predicting visual search in human-computer interaction

A minimal model for predicting visual search in human-computer interaction

Investigating User Attention and Interest in Websites

Design factors affecting relevance judgment behaviour in the context of metadata surrogates

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