Cognitive Engineering .1 Introduction .1 Introduction

Cognitive Engineering arose during the 1980s caused by the increased complexities and challenges faced by human operators, as computer technologies became ubiquitous in the workplace and changed the nature of work (Woods, 1987). Cognitive Engineering offers a principled approach to the design and development of human centred systems (Pfautz and Roth, 2006). Researchers in cognitive engineering have addressed problems like the decision making and problem solving support via computer systems in domains like military systems, aviation, manufacturing, process control, and medicine.

Fundamental to the research is the emphasis on an interacting triad of humans, the system to be acted upon, and the manner in which the humans view and control the system (Woods, 1987; Woods and Roth, 1988). Thereby, the inherent goal of the interaction design is a mediation that augments rather than limits humans’ view and control of humans within the system (Bisantz, 2006).

Cognitive engineering is also an interdisciplinary approach to designing computerized systems intended to support human performance (Roth et al, 2008). It is concerned with the analysis, design, and evaluation of complex socio-technical systems (Andriole and Adelman, 1995, Rasmussen et al., 1994, Woods and Roth, 1988, and Vicente, 2003). The methods of cognitive engineering consider workers and the tasks they perform as the central drivers for system design and provide a framework of how people perform cognitive work.

Bonaceto and Burns (2003) describe a number of cognitive engineering methods for system design and/or system evaluation, and group them into categories according to their intended purpose. Each method can be organized into one of five primary categories: (1) describing cognitive/behavioural processes, (2) modelling/simulating cognitive processes, (3) modelling/ simulating behavioural processes, (4) modelling erroneous actions, and (5) modelling human-machine systems. While some methods overlap multiple categories, each method is assigned to a "primary" category (Figure 9).

Chapter 3: Human Decision Making and Decision Support

COGNITIVE ENGINEERING METHODS

Cognitive and Behavioural Processes

Described with System Evaluation Methods Described with Theoretical Frameworks

Cognitive Processes

Modelled with Cognitive Task Analysis Simulated with Computational Cognitive Modelling

Behavioural Processes

Modelled with Task Analysis

Simulated with Computational Task Simulation Erroneous Actions Modelled with Human Reliability Analysis

Human-Machine Systems

Modelled with System-Oriented Methods Modelled with Cognitively-Oriented Methods FIGURE 9: COGNITIVE ENGINEERING METHODS (SOURCE: BONACETO AND BURNS, 2003)

Cognitive analysis also needs to satisfy a number of analytical aspects, if design information for innovative decision support is required (Potter, 2006). He mentions criteria like:

• Cognitive analysis must be far more than knowledge elicitation.

• Cognitive analysis must capture the fundamentals of the work domain and resulting decision making.

• Cognitive analysis must systematically transform knowledge elicitation into a set of complementary analytic artefacts.

• Cognitive analysis must serve as the basis for innovative decision support system design concepts.

Viewing the A-CDM implementation concept however reveals that so far focus has been placed on the organisational aspects. While such an approach is useful for the study of how the processes of information exchange and interactions with airports partners should look, it is argued that the confinement of cognitive aspects in these attempts could fundamentally contribute to turn-round problem solving: Given the fact that many work activities are inherently cognitive, e.g. decision makers have to process information, solve problems, predict TOBT, and make decisions, it is also argued that an understanding is required of how work activities are performed at current level of A-CDM implementation in order to design information systems that can support both cognitive activities and social interactions. Therefore, a cognitive analysis and

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engineering approach is proposed for the analysis of the A-CDM turn-round concept, because such an approach comprises a variety of methods to describe, model, and simulate cognitive and behavioural processes for the design of human-machine systems.

3.3.2 Selection of a Cognitive Engineering Method

In order to find the most suitable method for the objectives of this study, the range of factors that should be considered when choosing an engineering method as proposed by Stanton (Stanton et al, 2006) was evaluated. These include:

• the accuracy of the method;

• the criteria to be evaluated, such as time, errors, communications, movement, usability, etc;

• the acceptability and appropriateness of the methods to the people being analysed;

• the domain context;

• the resources available; and

• the cost-benefit of the method.

The selection of the method applied was also based on the factors proposed by Annett and Stanton (2000) that included:

• How deep should the analysis be?

• Which methods of data collection should be used?

• How should the analysis be presented?

• Where is the use of the method appropriate?

• How much time/effort does each method require?

• How much, and what type of expertise is needed to use the method(s)?

• What tools are there to support the use of the method(s)?

• How reliable and valid is/are the method(s)?

The engineering methods that were assessed for the analysis comprised of 11 categories and included

• data collection techniques;

• task analysis techniques;

Chapter 3: Human Decision Making and Decision Support

• charting techniques;

• human error identification techniques;

• mental workload assessment techniques;

• situation awareness measuring techniques;

• interface analysis techniques;

• design techniques;

• performance time prediction/assessment techniques; and

• team performance analysis techniques.

The main aim during the selection was to find a method that is useful in providing a valid and reliable output. Thereby, a main selection criterion was the usage of the gained knowledge: while e.g. psychologists need to get a better understanding of the cognitive functioning, the usage for the research project however had practical objectives. The findings should contribute to provide intelligent decision support and countermeasures for inaccurate TOBT predictions. Therefore, each method was assessed against the characteristics inherent in the A-CDM work system and the possible output of the analysis applied. A process model proposed by Stanton (Stanton et al., 2006) was used as a strategy for deciding what methods to use in, and how to adapt to the domain context (Figure 10). Annett et al. (2000) points out that care and skill is required in developing an approach for analysing the problem, formulating the intervention, implementing the intervention, and determining the success of the intervention.

FIGURE 10: VALIDATING THE METHODS SELECTION (SOURCE: STANTON, 2006)

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Hence, a method from the category Human-Machine System was used for the analysis of the A-CDM work system. Such a method considers how the entire system, consisting of all the machines and all the humans, is supposed to work as a whole in order to accomplish the overall system goal. In contrast, more traditional human factors approaches are primarily focused on determining what role individual human operators in the system will play (system-oriented methods).

From the category Human-Machine Systems, cognitively oriented methods such as the Cognitive Work Analysis (CWA) focus on the fundamental characteristics of the work domain and the cognitive demands that are imposed on humans operating in those domains. These methods complement the Cognitive Task Analysis and Knowledge Elicitation methods by mapping out the structure and purpose of the domain, allowing analysts to identify which cognitive strategies arise from actual domain demands and which are workarounds due to poorly designed systems (Bonaceto and Burns, 2003).

The CWA was therefore chosen as an overall framework and provided a conceptual structure for gathering, analysing, and structuring the required system knowledge and system functionality. Figure 11 shows the conceptual structure that was used as the basis for the analysis during the project:

FIGURE 11: APPLIED CONCEPT FOR THE PURSUED ANALYSIS (SOURCE: POTTER, 2006) KNOWLEDGE

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The analysis of A-CDM turn-round process was thus performed at a whole-system level. The focus thereby is not the role of the individual operator within A-CDM, but the fundamental characteristics of the A-CDM work domain and the cognitive demands that are imposed on humans operating within the system.

3.4 Cognitive Work Analysis