Human Factors: The Journal of the Human Factors and Ergonomics Society

Scaled worlds preserve certain functional relationships of a complex task environment while paring away others. The functional relationships preserved are defined by the questions of interest to the researcher. Different scaled worlds of the same task may preserve and pare away different functional relationships. In this paper we use the example of Ned to discuss the use of scaled worlds in applied cognitive research. Ned is based on a detailed cognitive task analysis of submarine approach officers as they attempt to localize an enemy submarine hiding in deep water. For Ned we attempted to preserve the functional relationships inherent in the approach officer's information environment while paring away other aspects of his task environment. Scaled worlds attempt to maintain the realism inherent in the preserved functional relationship while being tractable for the researcher and engaging to the participant.

The purpose of this investigation was to describe and evaluate an event-based knowledge elicitation technique. With this approach experts are provided with deliberate and controlled job situations, allowing investigation of specific task aspects and the comparison of expert responses. For this effort a videotape was developed showing an instructor pilot and student conducting a training mission. Various job situations were depicted in the video to gather information pertinent to understanding team situational awareness. The videotape was shown to 10 instructors and 10 student aviators in the community, and responses to the videotape were collected using a questionnaire at predetermined stop points. Consistent with expectations, the results showed that more experienced respondents (i.e., instructors) identified a richer database of cues and were more likely than students to identify strategies for responding to the situations depicted, providing some empirical evidence for the validity of the event-based technique. This method may serve as a useful knowledge elicitation technique, especially in the later stages of a job analysis when focused information is sought.

A fundamental challenge in studying cognitive systems in context is how to move from the specific work setting studied to a more general understanding of distributed cognitive work and how to support it. We present a series of cognitive field studies that illustrate one response to this challenge. Our focus was on how nuclear power plant (NPP) operators monitor plant state during normal operating conditions. We studied operators at two NPPs with different control room interfaces. We identified strong consistencies with respect to factors that made monitoring difficult and the strategies that operators have developed to facilitate monitoring. We found that what makes monitoring difficult is not the need to identify subtle abnormal indications against a quiescent background, but rather the need to identify and pursue relevant findings against a noisy background. Operators devised proactive strategies to make important information more salient or reduce meaningless change, create new information, and off-load some cognitive processing onto the interface. These findings emphasize the active problem-solving nature of monitoring, and highlight the use of strategies for knowledge-driven monitoring and the proactive adaptation of the interface to support monitoring. Potential applications of this research include control room design for process control and alarm systems and user interfaces for complex systems.

We propose that considering four categories of task factors can facilitate knowledge elicitation efforts in the analysis of complex cognitive tasks: materials, strategies, knowledge characteristics, and goals. A study was conducted to examine the effects of altering aspects of two of these task categories on problem solving behavior across skill levels: materials and goals. Two versions of an applied engineering problem were presented to expert, intermediate, and novice participants. Participants were to minimize the cost of running a steam generation facility by adjusting steam generation levels and flows. One version was cast in the form of a dynamic, computer-based simulation that provided immediate feedback on flows, costs, and constraint violations, thus incorporating key variable dynamics of the problem context. The other version was cast as a static computer-based model, with no dynamic components, cost feedback, or constraint checking. Experts performed better than the other groups across material conditions, and, when required, the presentation of the goal assisted the experts more than the other groups. The static group generated richer protocols than the dynamic group, but the dynamic group solved the problem in significantly less time. Little effect of feedback was found for intermediates, and none for novices. We conclude that demonstrating differences in performance in this task requires different materials than explicating underlying knowledge that leads to performance. We also conclude that substantial knowledge is required to exploit the information yielded by the dynamic form of the task or the explicit solution goal. This simple model can help to identify the contextual factors that influence elicitation and specification of knowledge, which is essential in the engineering of joint cognitive systems.

Troubleshooting is often a time-consuming and difficult activity. The question of how the training of novice technicians can be improved was the starting point of the research described in this article. A cognitive task analysis was carried out consisting of two preliminary observational studies on troubleshooting in naturalistic settings, combined with an interpretation of the data obtained in the context of the existing literature. On the basis of this cognitive task analysis, a new method for the training of troubleshooting was developed (structured troubleshooting), which combines a domain-independent strategy for troubleshooting with a context-dependent, multiple-level, functional decomposition of systems. This method has been systematically evaluated for its use in training. The results show that technicians trained in structured troubleshooting solve twice as many malfunctions, in less time, than those trained in the traditional way. Moreover, structured troubleshooting can be taught in less time than can traditional troubleshooting. Finally, technicians learn to troubleshoot in an explicit and uniform way. These advantages of structured troubleshooting ultimately lead to a reduction in training and troubleshooting costs.

In their search for generalizable behavioral patterns and design principles, cognitive field researchers should reflect on the epistemological limitations of empirical studies. In this paper we describe a framework for epistemological analysis that can help serve this purpose and discuss its application to two prototypical cases of cognitive engineering research: laboratory experiments and field studies. The framework examines two, often implicit, processes in empirical research: the abstraction from empirical data and the substantiation of theoretical constructs and principles. By explicitly considering these two processes in several systematic steps, we can gain appreciation for the epistemological contribution of empirical studies to cognitive engineering research. The framework and its application also provide guidance to such important issues as generalizability of results and external validity. Possible applications of this research include providing guidance to researchers and practitioners in evaluating design principles or conducting field studies.

We developed an integrative perspective on the empirical evidence supporting the influence of particular variables on the warning process based on a broad review of the warning literature. The warning process is described in terms of the following four components: notice, encode, comprehend, and comply. Relevant variables are classified as person variables (characteristics of the individual interacting with the warning) and warning variables (characteristics of the warning itself or the context in which the warning appears). This integrative perspective yields general principles about the variables that influence the warning process and serves as a resource for warning developers and as a guide to facilitate effective analysis of warnings. We also identify aspects of the warning process that are not well understood, directions for effective methods of intervention, and a research agenda for future efforts. Actual or potential applications of this research include improving the design of warnings.

We examined the influence of backrest inclination and vergence demand on the posture and gaze angle that workers adopt to view visual targets placed in different vertical locations. In the study, 12 participants viewed a small video monitor placed in 7 locations around a 0.65-m radius arc (from 65° below to 30° above horizontal eye height). Trunk posture was manipulated by changing the backrest inclination of an adjustable chair. Vergence demand was manipulated by using ophthalmic lenses and prisms to mimic the visual consequences of varying target distance. Changes in vertical target location caused large changes in atlanto-occipital posture and gaze angle. Cervical posture was altered to a lesser extent by changes in vertical target location. Participants compensated for changes in backrest inclination by changing cervical posture, though they did not significantly alter atlanto-occipital posture and gaze angle. The posture adopted to view any target represents a compromise between visual and musculoskeletal demands. These results provide support for the argument that the optimal location of visual targets is at least 15° below horizontal eye level. Actual or potential applications of this work include the layout of computer workstations and the viewing of displays from a seated posture.

Multioperator tasks often require complex cognitive processing at the team level. Many team cognitive processes, such as situation assessment and coordination, are thought to rely on team knowledge. Team knowledge is multifaceted and comprises relatively generic knowledge in the form of team mental models and more specific team situation models. In this methodological review paper, we review recent efforts to measure team knowledge in the context of mapping specific methods onto features of targeted team knowledge. Team knowledge features include type, homogeneity versus heterogeneity, and rate of knowledge change. Measurement features include knowledge elicitation method, team metric, and aggregation method. When available, we highlight analytical conclusions or empirical data that support a connection between team knowledge and measurement method. In addition, we present empirical results concerning the relation between team knowledge and performance for each measurement method and identify research and methodological needs. Addressing issues surrounding the measurement of team knowledge is a prerequisite to understanding team cognition and its relation to team performance and to designing training programs or devices to facilitate team cognition.