Bruce G. Coury

Status or Recommendation: Selecting the Type of Information for Decision Aiding

Decision aiding systems are becoming an important part of command and control. Selecting the best type of decision aiding information remains an important design decision. The research reported in this paper assesses the is to determine if a decision aid in an aircraft identification task should provide a recommendation for action or status information about the identity of the aircraft. Thirty-two subjects were equally divided into four groups: a control group where no decision aiding information was provided; a group who received only status information; a third group who received only recommendation information; and a fourth group who received both status and recommendation information. Results indicated that, in general, providing decision aiding information reduced the time required to identify the aircraft. Differences among the three types of decision aiding information occurred under those conditions when the decision aid was incorrect. When the decision aid provided inaccurate information, the group receiving only status information was least affected by the decision aid and was best able to correctly identify the aircraft. Recommendations for selecting the type of decision aiding information are discussed.

Effect of uncertainty and diagnosticity on classification of multidimensional data with integral and separable displays of system status

Integrative, objectlike displays have been advocated for presenting multidimensional system data. In this research two experiments assess the effect of uncertainty on the processing of integral and separable displays. In each experiment 30 subjects were trained to classify instances of system state into one of four state categories using a configural display, a bar graph display, or a digital display. In Experiment 1 the range of instances from the state categories was uniform; in Experiment 2 the distribution was biased toward those instances of highly uncertain state category membership. After training, subjects received extended practice classifying system data. In both experiments uncertainty was found to have the greatest effect on classification performance. In Experiment 1 the bar graph display was consistently superior; the configural display was superior to the digital display only under conditions of low uncertainty. In Experiment 2 the superiority of the bar graph display diminished, producing results equivalent to those of the digital display, with the configural display producing the worst performance. The effect of uncertainty on classification performance is discussed, with specific attention paid to the apparent configural and separable properties of the bar graph display.

Time stress and the processing of visual displays.

Selecting the appropriate display format for time-constrained tasks is the focus of the research presented in this paper. The effect of time stress on operator performance was assessed by manipulating the time available to process the display. Twenty people were trained as operators and instructed to identify the state of a system using either a digital display or a polygon display. Participants were required to reach a prespecified criterion in training and were then tested under?. time-constrained conditions. Time constraints were set at 100%, 50%, and 25% of each persons mean unpaced response times obtained during training. Results showed that response to the time constrained conditions was significantly affected by uncertainty and the type of display format. Discussion focuses on the effects of time stress on performance and the selection of displays for time-constrained tasks.

The effects of pacing on complex decision-making inspection performance.

The effects of time constraints in a complex decision-making inspection task were assessed utilizing a number of performance, physiological, and subjective measures. Twelve subjects were trained to classify a simulated product into one of four quality control categories, then tested on six pacing conditions varying in pacing speed and pacing rigidity. Subjects were able to maintain classification accuracy despite considerable variations in the time constraints of the task. The index of mental effort—heart rate variability—was the only measure which was found to be sensitive to the differences in pacing conditions. The subjective measures were not affected by pacing conditions but exhibited trends toward increasing postural discomfort, fatigue and boredom from the beginning to the end of each condition. A model of the inspector is tested which is based upon resource-limited models of human information processing.

Graphical Displays for Orientation Information

New technology for submarine periscopes requires that all information be presented on a graphics workstation. The research presented in this paper is concerned with the design of periscope workstation displays for orientation information. In this experiment 24 people made judgments of orientation using three types of component displays (submarine, periscope, and relative) and two types of worldviews (north-up and track-up). Results revealed that the judgments of orientation were best with the north-up display, with relative questions the most difficult to make. When rotations were required for a response, characteristic mental rotation curves were found. The results are discussed in terms of factors affecting the design of displays for orientation information, selecting the best display format for the periscope workstation, and the processing strategies used to process orientation information.

Probing the mental models of system state categories with multidimensional scaling

Abstract Identifying the underlying decision criteria used by people to classify system state is one of the major challenges facing designers of decision aids for complex systems. This research describes the use of multidimensional scaling (MDS) to probe the structure and composition of the mental models employed by users to identify system state, and to evaluate the impact of different display formats on those models. Twenty people were trained to classify instances of system data. Pairwise similarity ratings of instances of system data were analysed by MDS to reveal the dominant dimensions used in the task. Results showed that significant individual differences emerged, and that the dimensions used by people were also a function of the type of display format.

Classification of Multidimensional Data under Time Constraints: Evaluating Digital and Configural Display Representations

The purpose of this research was to evaluate differences in processing ability between integral and separable representations of process control data under conditions of time constraints. Subjects were trained as “operators” to identify system states and subsequently participated in time constrained (100%, 50% and 25% paced) sessions. Findings revealed that operators in both display conditions were able to respond significantly faster (while maintaining fairly high degrees of accuracy) under 100% and 50% time constrained conditions than in self-paced conditions. Classification accuracy suffered more for the separable than the integral display during the 25% paced condition.

Multidimensional Scaling as a Method for Probing the Conceptual Structure of State Categories: An Individual Differences Analysis

Identifying the underlying decision criteria used by operators to classify system state, and revealing the way in which that information is internally represented is one of the challenges facing designers of control systems. This paper describes the use of multidimensional scaling (MDS) to probe the structure and composition of the internal conceptual models used by operators to identify system state. Specifically, the issue of individual differences in mental model is addressed, as well as the impact of these differences on individual performance in a classification task. Twenty subjects were trained as operators to classify instances of system data into one of four system state categories. After training, subjects were asked to rate the similarity between instances of system state. Results showed that the dominant dimensions used by an individual are related to his/her performance on the classification task.

Cognitive Models of Planning in the Design of Project Management Systems

The research presented in this paper is concerned with the planning component of project management and describes the use of interviewing and observational techniques to develop cognitive models of planning for project management systems. Interviews were conducted with six project managers from six different problem domains. Protocol analysis was used to develop two types of cognitive models: process models that provided detail descriptions of planning actions; and a higher level model of the planning process based on the Hayes-Roth theoretical model of planning. A visual representation of the planning process, called DMAP, was created to identify the type planning that occurs at each stage of the planning process in project management. The discussion focuses on the use of cognitive models in the design of knowledge-based systems for project management.

The Bargraph as a Configural and a Separable Display

The results from two experiments demonstrate the conditions under which a bargraph display can be processed both as a configural display and as a separable display. When there is a unique mapping of display attributes to system state categories (Experiment 1), the perceptual cues in the bargraph display serve to produce superior classification performance. Once that mapping and predictability is disrupted (Experiment 2), operators resort to analyzing the bargraph display in a separable fashion and produce performance equivalent to the serially processed digital display. Uncertainty (i.e., the degree to which a value or set of values of process variables map to a single system state) appears to be the primary factor affecting the way in which the bargraph display will be processed.