Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

Dimensions of air traffic control tower information needs: from information requests to display design.

In an effort to determine the information needs of tower air traffic controllers, instructors from the Federal Aviation Administration's Academy in Oklahoma City were asked to control traffic in a high-fidelity tower cab simulator. Information requests were made apparent by eliminating access to standard tower information sources. Instead, controllers were required to ask for precisely the information they needed during the scenarios. The information requests were classified using an elaboration of Zwaan and Radvansky's (1998) dimensions of situation models. The vast majority of requests were about three of the dimensions originally developed for reading comprehension: the protagonist, intentionality, and space. The information requests were also classified into 28 operational categories (e.g., aircraft identification, destination). From these results, the data were summarized, not just statistically, but by the creation of display-hypotheses. The display-hypotheses were organized according to the situation-model dimensions. Controllers preferred data blocks organized by the situation-model principle over those that violated this organization. The summary display-hypotheses were quite simple and accounted for the vast majority of the information requests controllers made. The display-hypotheses accounted for the information needs of controllers during routine as well as off-nominal events.

Linking task analysis to information relevance.

OBJECTIVE: The main objective of this study is to present a methodology for computing information relevance. BACKGROUND: Relevance is a pervasive term used in several domains, such as pragmatics, information science, and psychology. Quantifying the relevance of information can be helpful in effective display design. Displays should be designed so that the more relevant information is more easily accessed. METHOD: This procedure focuses on computing the relevance of a piece of information by taking into account three aspects of tasks that use the information: the number of different tasks that make use of the information, the frequency of occurrence of those tasks, and the criticality of those tasks. The methodology can be used to compute the aggregate relevance of a piece of information for a particular component of a system or for the entire system. This methodology was illustrated using the domain of air traffic control (ATC). RESULTS: In support of the validity of the methodology, we were able to confirm the value of weather information and traffic information in ATC towers. CONCLUSION: The method can be used to derive information relevance, a characteristic of information that has implications for display design for any domain. APPLICATION: Designers can use information about aggregate relevance to design information displays that feature the most relevant information.

The use of flight progress strips while working live traffic: frequencies, importance, and perceived benefits.

The Federal Aviation Administration's effort to automate air traffic control (ATC) requires that the functionality provided today be captured in future systems. We report the first quantitative naturalistic observation of paper flight progress strip interactions during operational use. Strip use was similar in a variety of situations, but some uses varied as a function of altitude, staffing, or the cooperative style used by controller teams. Design of automation should proceed by prioritizing changes based on frequency of use and importance and should ensure that an effective method of interacting with flight information is incorporated. In addition to applied relevance to the ATC domain, the results touch on several theoretical concerns relevant to dynamic environments. Actual and potential applications of this research include the establishment of a database of strip activity and an arsenal of information valuable to system designers.

Individual differences in working memory capacity predict visual attention allocation.

To the extent that individual differences in working memory capacity (WMC) reflect differences in attention (Baddeley, 1993; Engle, Kane, & Tuholski, 1999), differences in WMC should predict performance on visual attention tasks. Individuals who scored in the upper and lower quartiles on the OSPAN working memory test performed a modification of Egly and Homa's (1984) selective attention task. In this task, the participants identified a central letter and localized a displaced letter flashed somewhere on one of three concentric rings. When the displaced letter occurred closer to fixation than the cue implied, high-WMC, but not low-WMC, individuals showed a cost in the letter localization task. This suggests that low-WMC participants allocated attention as a spotlight, whereas those with high WMC showed flexible allocation.