Human Performance Engineering

The overall objective of this article is to explore the psychological theories of ‘thinking’ and the efficacy and efficiency of each of these theories for the purpose of innovation and creativity. We know for sure that some people, companies and businesses are better at problem solving, decision making and innovation than others and we also know (with sufficient data proofs) that most of these ‘some’ entities have been doing so consistently. Therefore, one must ask himself/herself the question as to how these entities are consistently able to adopt themselves better than others. And given the fact, that adaptation is the primary characteristic of intelligence, one has to ask himself/herself as to, where does this intelligence comes from? Is this form and degree of cognitive intelligence inherent with certain people? Can it be learned and acquired? What is the reason behind this dissimilar ability for adaptability and innovation? I argue that the answers to these questions, exists in-parts in different researches and literature. The objective for this article is to explore some of the theories that are associated with the notion of ‘cognitive thinking’.

IEEE Expert / IEEE Intelligent Systems, 1987

Hubert Dreyfus has acquired a reputation as being one of the most vehement and outspoken critics of the goals and accomplishments of research in artificial intelligence. The recently published book by Hubert and Stuart Dreyfus, Mmd over Machine, expands upon the theme expressed in earlier works [2] that AI systems are based upon an overly simplistic model of human problem solving and as a result will never achieve levels of performance approaching those of human beings.

Interfaces, 1987

The MS/OR community has, as its common mission, the development of tools and procedures to improve problem solving and decision making. This report discusses the advances needed to combine human thinking with intelligent machines to achieve a more productive society. Areas of high potential include research in expert systems, conflict resolution, agenda setting, decision making in an organizational setting, and empirical studies of individual behavior. The resources currently being applied to research in decision making and problem solving are modest and are not commensurate with the opportunities or the human resources available for exploiting them.

Journal of Cognitive Engineering and Decision Making, 2007

The field of cognitive engineering and decision making (CEDM) has grown rapidly in recent decades. At this writing, it is the largest technical interest group within the Human Factors and Ergonomics Society. Work that falls into this area of research and study is also widely practiced across Europe and in countries around the world. Along with this growth, there is a significant need for a peer-reviewed journal that focuses specifically on CEDM as a science and applied discipline. The Journal of Cognitive Engineering and Decision Making is intended to meet that need. It will cover current research, theory, and practice in ways that not only provide for the sharing of information across interested parties but also serve to move the field forward. This will advance theoretical bases; address outstanding scientific challenges; set new courses and directions; address methods, measurement, and methodological issues; and show useful applications of this work in the development of operational and training systems in many domains that are of significance to society, government, and business. In this article, we provide background on the CEDM field and its areas of research. We use this as a platform for further specifying the scope of this journal along three technical tracks. Objectives are identified for each track as it supports the overall mission of the journal. Finally, we provide information on an electronic companion to the journal that is intended to support advances in the field through dialogue and access to further resources.

Systems engineering is conventionally defined as a multidisciplinary approach to the realization of successful systems. There is opportunity to further strengthen and improve the practice of systems engineering by increasing the use of cognitive sciences analysis in the practice of systems engineering. The goal of this paper is facilitate this improvement by providing a framework for incorporating additional cognitive sciences analysis in systems engineering decisions. Case studies show that imperfect decisions with cognitive roots have contributed to notable accidents. Ironically, most sources limit their disciplines to technological and managerial processes, mentioning cognitive sciences only in a benign context. Cognitive science is a sub-discipline of psychology, focusing on mental processing. In this paper we focus on two sub domains of cognitive sciences, cognitive bias and social constructionism. Existing sources discuss cognitive aspects of systems engineering but in general devote little attention to those aspects that may have catastrophic consequences. This paper suggests that these disciplines play a larger role than is generally recognized, particularly with respect to decision making which is a standard part of systems engineering. The decisions discussed in this paper pertain both to those made by executives and by operators in the operational phase of a system. Decision making is one area that may have such consequences; this is the area that will be emphasized in this paper. In addition, case studies show that, in addition to design decisions, imperfect decisions with cognitive roots have contributed to notable accidents. Two major approaches suggested by other sources for improving the decision making process are improved leadership and independent review. This paper suggests that both of these approaches offer promise if rigorously implemented but have their own flaws that need to be overcome. However, the need for improved decision making and a study into the conditions that lead to the flawed decisions suggest that a deeper look into these and other approaches is desirable. This paper examines barriers to safe operation due to decision errors, and proposes a framework for remedies.

British Journal of Educational Technology, 2011

Serious games have a great potential for training and educating people in novel and engaging ways. However, little empirical research has been done on the effectiveness of serious games and, although early findings do point in a moderately positive direction, even less is known about why some games succeed in effectively educating while others don't. We therefore propose a serious game, Code Red: Triage, which is designed to empirically test a number of cognition-based design guidelines in the context of crisis management training. Our purpose is to come to a set of design guidelines through empirical experiments that enhance the instructional design of serious games and can be used in the development of future games.

Advances in Human Performance and Cognitive Engineering Research

1999

Military operations during the last thirty years have shifted from conventional modes of warfare with wellunderstood adversaries towards warfare characterized by shorter warning times, greater ambiguity and the requirement to plan and execute responses in a greatly reduced time frame. While dramatic innovations in technology significantly extend information processing capabilities, the critical -and often the most vulnerablecomponents in command and control (C') systems remain the human decision makers. As advanced decision support technologies permeate operational units, today's military forces face tremendous challenges in simultaneously evolving effective organizational processes, education and training, and advanced information technology. The increased pressure on C2 systems emphasizes the need for more comprehensive "decision system" modeling relating the multiple components of C2 decision making to system effectiveness.

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