Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models
01 May 1983-Vol. 13, Iss: 3, pp 257-266
TL;DR: A discussion is presented of the requirement for different types of models for representing performance at the skill-, rule-, and knowledge-based levels, together with a review of the different levels in terms of signals, signs, and symbols.
Abstract: The introduction of information technology based on digital computers for the design of man-machine interface systems has led to a requirement for consistent models of human performance in routine task environments and during unfamiliar task conditions. A discussion is presented of the requirement for different types of models for representing performance at the skill-, rule-, and knowledge-based levels, together with a review of the different levels in terms of signals, signs, and symbols. Particular attention is paid to the different possible ways of representing system properties which underlie knowledge-based performance and which can be characterised at several levels of abstraction-from the representation of physical form, through functional representation, to representation in terms of intention or purpose. Furthermore, the role of qualitative and quantitative models in the design and evaluation of interface systems is mentioned, and the need to consider such distinctions carefully is discussed.
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01 Jan 1993
TL;DR: This guide to the methods of usability engineering provides cost-effective methods that will help developers improve their user interfaces immediately and shows you how to avoid the four most frequently listed reasons for delay in software projects.
Abstract: From the Publisher:
Written by the author of the best-selling HyperText & HyperMedia, this book provides an excellent guide to the methods of usability engineering. Special features: emphasizes cost-effective methods that will help developers improve their user interfaces immediately, shows you how to avoid the four most frequently listed reasons for delay in software projects, provides step-by-step information about which methods to use at various stages during the development life cycle, and offers information on the unique issues relating to informational usability. You do not need to have previous knowledge of usability to implement the methods provided, yet all of the latest research is covered.
11,929 citations
TL;DR: In this article, the results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed, including task-, behavior-, and subject-related correlates of subjective workload experiences.
Abstract: The results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed. Subjective evaluations of 10 workload-related factors were obtained from 16 different experiments. The experimental tasks included simple cognitive and manual control tasks, complex laboratory and supervisory control tasks, and aircraft simulation. Task-, behavior-, and subject-related correlates of subjective workload experiences varied as a function of difficulty manipulations within experiments, different sources of workload between experiments, and individual differences in workload definition. A multi-dimensional rating scale is proposed in which information about the magnitude and sources of six workload-related factors are combined to derive a sensitive and reliable estimate of workload.
11,418 citations
TL;DR: This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives, and considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust.
Abstract: Automation is often problematic because people fail to rely upon it appropriately. Because people respond to technology socially, trust influences reliance on automation. In particular, trust guides reliance when complexity and unanticipated situations make a complete understanding of the automation impractical. This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives. It considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust. The context in which the automation is used influences automation performance and provides a goal-oriented perspective to assess automation characteristics along a dimension of attributional abstraction. These characteristics can influence trust through analytic, analogical, and affective processes. The challenges of extrapolating the concept of trust in people to trust in automation are discussed. A conceptual model integrates research regarding trust in automation and describes the dynamics of trust, the role of context, and the influence of display characteristics. Actual or potential applications of this research include improved designs of systems that require people to manage imperfect automation.
3,105 citations
Cites methods from "Skills, rules, and knowledge; signa..."
...The analytic process is similar to knowledge-based performance, as described by Rasmussen (1983), in which information is processed and plans are formulated and evaluated using a function-based mental model of the system....
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TL;DR: It is argued that risk management must be modelled by cross-disciplinary studies, considering risk management to be a control problem and serving to represent the control structure involving all levels of society for each particular hazard category, and that this requires a system-oriented approach based on functional abstraction rather than structural decomposition.
2,547 citations
Cites methods from "Skills, rules, and knowledge; signa..."
...This problem has led to development of the skill-, rule-, knowledge-based behaviour model of cognitive control (Rasmussen, 1983) and the more recent paradigms of 'naturalistic' decision making (For a review, see Klein et al., 1994)....
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TL;DR: The origins and contributions of the naturalistic decision making research approach, which has been used to improve performance through revisions of military doctrine, training that is focused on decision requirements, and the development of information technologies to support decision making and related cognitive functions.
Abstract: Objective: This article describes the origins and contributions of the naturalistic decision making (NDM) research approach. Background: NDM research emerged in the 1980s to study how people make decisions in real-world settings. Method: The findings and methods used by NDM researchers are presented along with their implications. Results: The NDM framework emphasizes the role of experience in enabling people to rapidly categorize situations to make effective decisions. Conclusion: The NDM focus on field settings and its interest in complex conditions provide insights for human factors practitioners about ways to improve performance. Application: The NDM approach has been used to improve performance through revisions of military doctrine, training that is focused on decision requirements, and the development of information technologies to support decision making and related cognitive functions.
2,224 citations