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Relationships among display features, eye movement characteristics, and reaction time in visual search.

Article Excerpt
INTRODUCTION

The question of what determines the location of the next fixation, or how people select the fixation point as they move their eyes around a display in front of them, might be addressed with reference to the specific activities necessary for cognition. In daily life, the retrieval of information is essential. Without this activity, nothing can be performed. The evaluation of eye movement characteristics and performance measures might add a new approach to the evaluation of the information retrieval strategy used by humans. In investigations of the effectiveness of a display design on which information retrieval is carried out, not only efficiency (performance) measures but also measures based on human eye movement characteristics are important.

Other studies have investigated eye movement characteristics to clarify a variety of cognitive processes. Althoff and Neal (1999) examined an eye-movement-based memory effect and showed different patterns of eye movement elicited by famous and nonfamous faces. They concluded that the eye-movement-based memory effect is the expected consequence of previous exposure to famous faces. Donk (1994) investigated human monitoring behavior in a multiple-instrument setting and showed that the spatial arrangements of the instruments on the display affected sampling behavior. He also found that human monitoring seemed to be biased by a tendency toward sampling by means of horizontal transitions at the cost of diagonal transitions. Rayner (1995) suggested that the basic mechanism of eye movement control is similar across tasks (reading, scene perception, visual search, etc.) but that the trigger to move the eyes is different according to the specificity of the tasks. It has been suggested that eye movements should be used to study visual search. Actually, several studies have paid attention to the number of saccades occurring during search and their fixation durations (Engel, 1977; Gould & Dill, 1969; Luria & Strauss, 1975; Megaw & Richardson, 1979; Scinto, Pillalamarri, & Karsh, 1986). Thus eye movement characteristics are useful in investigating a variety of cognitive process by decomposing search into spatial and temporal components.

Zelinsky and Sheinberg (1995) attempted to model reaction time in serial and parallel search tasks (Treisman & Gormican, 1988) using eye movement characteristics such as the number of saccades and their fixation duration. They discussed factors that underlie an increase in search time and proposed two models: the variable number model and the variable duration model. They proposed that visual search behavior might be understood as an interaction between two underlying processes--the number of search movements preceding a judgment (the variable number model) and the time taken to initiate these movements (the variable duration model)--and that using the number of fixations and the fixation duration would be effective to increase understanding of visual search behavior.

The variable number model predicts that increasing the difficulty of the search task should result in more search movements. According to the variable duration model, as the difficulty of a search task increases, more processing time is devoted to each search movement but the overall number of search movements should remain about the same. They showed that search time could be reliably (R = .92) predicted by the number of eye movements the participant performed to search the display and by the latency of the initial saccades. However, they did not discuss whether their data supported a mediational model, in which reaction time is mediated by eye movement characteristics, and display features were not directly related to reaction time. In other words, they did not clarify whether the effects of display features on reaction time were attributable solely to eye movement characteristics. Until now, it has not been clarified whether or not a mediational model is supported in visual search tasks.

When applying a multiple regression model, Zelinsky and Sheinberg (1995) did not analyze the parallel and serial search tasks separately. Analyzing the parallel and serial search tasks separately is important in investigating the underlying cognitive process for different search tasks. Given the fact that the number of saccades and their fixation duration are important in describing reaction time in visual search tasks, it is not sufficient to describe the relationship between these eye movement characteristics and search time. How the interaction between number of fixations and fixation duration changes as a function of the display features must be explored in more detail in order to investigate some underlying cognitive processes using eye movement characteristics. In this way, visual search behavior can be better understood and displays can be designed to accurately fit human visual information processing, including perceptual and cognitive aspects.

When information is presented on a CRT display, it is well known that the grouping of information leads to improved search efficiency. In graphical user interfaces (GUIs), an icon interface is effectively used for transmitting the contents of a task to computer users. In investigations of performance measures such as search time or accuracy, the icon interface and spatial grouping seem to increase scanning speed. Brand and Orenstein (1998) investigated the effect of spatial grouping on scanning speed in a matching task. Niemela and Saarinen (2000) investigated how participants looked for a target file among distractor files in an icon-based human-computer interface. Both the presence of icons and their grouping had a significant positive effect on scanning speed. Tullis (1983) proposed a method to define character-based layout complexity. Parush, Nadir, and Shtub (1998) proposed a method to calculate layout complexity on GUIs and evaluated various types of displays. Their results showed that display type, organization (grouping), and layout complexity are features that influence eye movements. However, these studies did not explore how display features and eye movements are related to search time. Understanding how display features and eye movement characteristics are related to search time in visual...

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