Task analysis cognitive techniques

The term Task Analysis (TA) can be applied very broadly to encompass a wide variety of human factors techniques. Nearly all task analysis techniques provide, as a minimum, a description of the observable aspects of operator behavior at various levels of detail, together with some indications of the structure of the task. These will be referred to as action oriented approaches. Other techniques focus on the mental processes that imderlie observable behavior, for example, decision making and problem solving. These will be referred to as cognitive approaches. 

The IMAS technique described above is useful, in that it addresses aspects of operational skills, that is, diagnostic and problem solving abilities, that are not covered by other techniques. To that extent it can be regarded as a method of cognitive task analysis. It is not essential to use a computer program to obtain useful results. The mental models produced by IMAS can be elicited by pencil and paper methods. Nevertheless interpretation and application of the results require some expertise. 

The human factors literature is rich in task analysis techniques for situations and jobs requiring rule-based behavior (e.g., Kirwan and Ainsworth 1992). Some of these techniques can also be used for the analysis of cognitive tasks where weU-practiced work methods must be adapted to task variations and new circumstances. This can be achieved provided that task analysis goes beyond the recommended work methods and explores task variations that can cause failures of human performance. Hierarchical task analysis (Shepherd 1989), for instance, can be used to describe how operators set goals and plan their activities in terms of work methods, antecedent conditions, and expected feedback. When the analysis is expanded to cover not only normal situations but also task variations or changes in circumstances, it would be possible to record possible ways in which humans may fail and how they could recover from errors. Table 2 shows an analysis of a process control task where operators start up an oil refinery furnace. This is a safety-critical task because many safety systems are on manual mode, radio communications between control room and on-site personnel are intensive, side effects are not visible (e.g., accumulation of fuel in the fire box), and errors can lead to furnace explosions. 

The task analysis technique has been developed mainly to handle human factors (in HAZID and other methods). In HAZID this is helpful in addressing human factors such as human error, man—machine interface, and procedural error. Of the various hazard identification techniques, task analysis is one of the most important. The other techniques are discussed in subsequent chapters, but here discussions will be on task analysis. Task analysis is the study of what users need to do, in terms of actions and/or cognitive processes, to achieve a task objective. There are several factors, such as task duration, repetitive frequency, task allocation, complexity, equipment, ambience, and environmental conditions, which are required for the task and they very much influence the performance. At times, tasks are often used interchangeably with process. 

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The results of CTA are usually cast in the form of graphical representations that incorporate the work demands and user strategies. For cognitive tasks that have been encountered in the past, operators may have developed well-established responses that may need some modifications but nevertheless provide a starting framework. For unfamiliar tasks that have not been encountered in the past or are beyond the design-basis of the system, operators are required to develop new methods or combine old methods in new ways. To illustrate how the results of CTA can be merged in a graphical form, two techniques are presented hierarchical task analysis and the critical decision method. 

Once the required task data are determined, they need to be collected. Table 33.2 lists seven generic techniques for acquiring cognitive task data. The techniques are not mutually exclusive. For example, all techniques use some form of observation. Instrumented human-machine interface techniques and protocol analysis are used as knowledge-acquisition techniques. Each data-collection technique is described in more detail below. 

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