A Review of the Event Analysis of Systemic Teamwork Methodology

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HFIDTC/WP1.1.3/10 Version 2/ 31 October 2005 Related methods • Cognitive aspects of the task under analysis are not elicited using observational techniques. Verbal protocol analysis is more suited for collecting data on the cognitive aspects of task performance. • An observational study can be both difficult and expensive to set up and conduct. Gaining access to the required establishment is often extremely difficult and very time consuming. Observational techniques are also costly, as they require the use of expensive recording equipment (digital video camera, audio recording devices). • Causality is a problem. Errors can be observed and recorded during an observation but why the errors occur may not always be clear. • The analyst has a very low level of experimental control. • In most cases, a team of analysts is required to perform an observation study. It is often difficult to acquire a suitable team with sufficient experience in conducting observational studies. There are a number of different observational techniques, including indirect observation, participant observation and remote observation. Other related techniques include verbal protocol analysis, critical decision method, applied cognitive task analysis, walkthroughs and cognitive walkthroughs. All of these techniques require some sort of task observation. Observational data is also used as an input to numerous HF techniques, such as task analysis, human error identification, and charting techniques. Approximate training and application times Whilst the training time for an observational analysis is low (Stanton & Young 1999), the application time is normally high. The data analysis stage can be particularly time consuming. Kirwan & Ainsworth (1992) suggest that in the transcription process, 1 hour of audio recorded data would take approximately 8 hours to transcribe. Reliability and validity Observational analysis is beset by a number of problems that can potentially affect the reliability and validity of the technique. According to Baber & Stanton (1996) problems with causality, bias (in a number of forms), construct validity, external validity and internal validity can all arise unless the correct precautions are taken. Whilst observational techniques possess a high level of face validity (Drury 1990) and ecological validity (Baber & Stanton 1996), analyst or participant bias can adversely affect the reliability and validity of the techniques. Tools needed For a thorough observational analysis, the appropriate visual and audio recording equipment is necessary. Observational studies can be conducted using pen and paper, 33
HFIDTC/WP1.1.3/10 Version 2/ 31 October 2005 however this is not recommended, as crucial parts of data are often not recorded. For the data analysis process, a PC with the Observer software is required. 3.3 HTA – Hierarchical Task Analysis Background and Applications Hierarchical task analysis (HTA) (Annett 2004) is the most popular task analysis technique and has become perhaps the most widely used of all HF techniques. HTA involves describing the task under analysis through the break down of the task into a hierarchy of goals, sub goals, operations and plans. Goals are the unobservable task goals associated with the task in question, operations are the observable behaviours required to accomplish the task goals and plans are the unobservable decisions and planning made on behalf of the operator. The end result is an exhaustive description of task activity. HTA has been applied across a wide spectrum of domains, including the process control and power generation industries (Annett 2004), emergency services (Baber et al 2004) military applications (Kirwan & Ainsworth, 1992; Ainsworth & Marshall, 1998/2000), civil aviation (Marshall et al 2003), driving, public technology (Stanton and Stevenage 1998) and even retail (shepherd 2001). One of the main reasons behind the enduring popularity of HTA is its flexibility and the scope for further analysis of the sub-goal hierarchy that it offers to the HF practitioner. The majority of HF analysis methods either require an initial HTA of the task(s) under analysis as their input, or at least are made significantly easier through the provision of a HTA. HTA acts as an input into numerous HF analyses techniques, such human error identification (HEI), allocation of function, workload assessment, interface design and evaluation and many more. In a review of ergonomics texts, Stanton (2004) highlights at least twelve additional applications to which HTA has been put, including interface design and evaluation, training, allocation of functions, job description, work organisation, manual design, job aid design, error prediction and analysis, team task analysis, workload assessment and procedure design. Domain of application HTA was originally developed for the chemical processing and power generation industries (Annett 2004). However the technique is generic and can be applied in any domain. Procedure and advice Step 1: Define task under analysis The first step in conducting a HTA is to clearly define the task(s) under analysis. As well as identifying the task under analysis, the purpose of the task analysis effort should also be defined. For example, Marshall et al (2003) conducted a HTA of a civil aircraft landing task in order to predict design induced error for the flight task in question. Step 2: Data collection process Once the task under analysis is clearly defined, specific data regarding the task should be collected. The data collected during this process is used to inform the development of the 34
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