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Developing Training Interventions

To summarise my position, a competent performance in a systems context requires an individual to apply classes of functions (competencies), enacted through specific activities and supported by underpinning knowledge, across a range of contexts. These functions need to be applied under conditions of increasing complexity, ambiguity and cognitive demand depending upon the operation’s proximity to the system boundary. As we have seen, an effective training regime must develop competence in relation to operational demands. If there is a mismatch between training provision and operational need then there is an elevated risk of crew responses to anomalies lacking efficacy. By implication, training ought to be informed by the safety management system, given that this is usually the source of information about operational risk. In this section, I want to consider how training can better support the development and maintenance of competence.

Conventional CRM training contains content drawn from social and cognitive psychology. Applied research in the field of aviation has grown enormously since CRM first emerged but it is questionable that this growing body of knowledge stands in relation to competence in the same way that the fundamentals of, say, meteorology might. At the ab initio level, there is possibly the space to deal with some of this content in depth but in-service, recurrent training is under such pressure that a true cost/benefit should be demonstrated before resources are allocated to interventions that simply address academic or underpinning knowledge. I do not wish to imply that knowledge of fundamental research is of no value but I suggest that this falls under the heading of self-development. Broadly speaking, conventional approaches to CRM training can be classified as:

Centralised (instructor-led, typically in a classroom)

Distributed (trainee-led, exploiting text or digital media, including video or programmed content (CBT))

Experiential (typically in a simulated environment of either low'- (desktop, part-task trainer) or high-fidelity (full-mission simulation))

Developments in technology offer opportunities for training to be more distributed while affording collaborative, high-fidelity experiences. Networked, remotely located training devices and operational equipment that can jointly participate in exercises have been commonplace in the military for many years. In aviation, training applications that allow' crew to rehearse cockpit drills using a virtual reality interface while, themselves, each being at remote, netw'orked locations are entering service. Technology is now' capable and affordable w'hile the software need to develop training applications is more accessible than in the past. Exploiting this technology does require access to a training design capability.

If competence is essentially about performance, it follows that training should provide opportunities to, first, act and then allow' for reflection. This premise suggests that training should be experiential whenever possible. Figure 11.6 show's a template design for a forced-choice event that formed part of a recurrent simulator session. On this occasion, the overall scenario w'as a standard company route with the aircraft on the return leg to home base. The route passed close by a third company destination. Fidelity w'as, therefore, high. The trigger event w'as a depressurisation, chosen because it happened to be a mandatory item to be covered during this cycle. The forced descent resulting from the technical problem meant that there was now'

Game decision tree

FIGURE 11.6 Game decision tree.

insufficient fuel to complete the remainder of the flight and so a diversion was necessary. There were two available airports. The first was the company destination and the second was still acceptable, if a little further away. The first steps in the design of the activity, then, are to select a plausible storyline (routine company sector), establish a trigger event which forces a response and then offer plausible alternatives. The goal is to design an activity that has face validity, which means that the scenario is sufficiently plausible such trainees can readily buy-in to the activity. We are trying to capitalise on learner motivation.

The next step is to define the attributes of the destinations. Runway direction, length, available navigation aids and surrounding topography were, in this case, set. The variables that can be manipulated are usually associated with the weather. Precipitation, visibility, wind strength and direction, implications for braking action can all be controlled. In this scenario, values were set such that no single destination or runway was obvious but all conditions were plausible, again in an attempt to establish face validity. The intent was to create situations that trainees would find recognisable based on past experience. Having created the scenario, the next step was to consult a group of SMEs. Management pilots were asked to step through the decision points and state the advantages and disadvantages of each choice. They were also asked to state what their preferred choice would be. The decision points in Figure 11.5 are described in Table 11.9.

The responses from the management pilots were aggregated and the most frequently cited reasons were used to create a table that could be used in the subsequent exercise debrief. Interestingly, the results were fed back to the management pilots and some were surprised that their peers, first, sometimes opted for a different outcome and, second, offered justifications that differed from theirs. Even subject matter experts do not always agree. Table 11.10 contains an example of the decision point strengths and weaknesses collected from the management pilots.

TABLE 11.9

Game Plan Decision Points

Decision Point

Action

1A

Land at Destination A

IB

Land at Destination В

2A

Execute go-around and second approach to Destination A

2B

Divert to Destination В

ЗА

Make approach to Runway 1

3B

Make approach to Runway 2

TABLE 11.10

Example of Decision Factors

Decision 1

Go to Destination 1

Not Go to Destinationl

Really should consider

Online port so faster service recovery Crew more familiar than with Destination 2 Closer than Destination 2

Weather close to minima Probability of a missed approach

Might also consider

Better able to deal with medical issues arising from depressurisation.

No terrain issues Autoland capability Fuel availability Long runway

No ILS on reciprocal runway Time available for preparation due to proximity

Landing performance (wet runway with tailwind)

The planning described here was then used to construct a simulator profile. Rules were established to ensure that the exercise always ended with a successful landing: we did not want crews to fail as that would undermine the training value. The debrief was then conducted using the SME framework so that crew could, first, declare their own decision-making process and then compare with the thoughts of an expert group. However, it was made clear that there was no correct solution. The point was to explore decision-making. Because of the way the exercise was constructed, crew had to trade-off options (into-wind runway with no instrument landing system (ILS) v ILS with tailwind; descend over terrain in marginal weather v descend over sea), prioritise (needs of injured passengers v probability of successful approach) and consider future risk (fuel remaining if unable to land on the first approach). They also had to fly the simulator and deal with the procedural activity associated with the task. The framework is representative of a LOFT scenario although possibly with some additional effort applied to designing the decision points. It also represents a template that can be used to map competence training goals onto technologies.

The choice of trigger event is important. In the exercise we have just looked at, the goal was to explore decision-making and not simply to deal with the malfunction. An over-emphasis on the technical aspects of the problem would have detracted from the point of the exercise. However, the nature of the trigger event is significant in that it can shape the exercise. The next exercise I want to look at explored how crews tradeoff activities. The trigger was an ambiguous report of a smell in the cabin, which prompted the use of the ‘smoke and fumes’ checklist. The exercise forced the crew to balance the management of normal and non-normal checklists while deciding about possible diversions and still control the aircraft trajectory. The trigger event was sufficiently vague but one that would have been familiar to crew. The aim of the exercise, in this case, was to explore task management. What was different this time is that the training medium used was a desktop simulation.

Figure 11.7 illustrates the materials used to create the scenario. Crews of a captain, FO and SO were provided with all relevant company documentation, charts for destinations, port pages and weather information. The aircraft was position on an airway en route to home base. Each hexagon on the grid represented a unit of distance and rules were developed that resulted in the activity running in almost real time. We removed the need for vertical navigation but crew' were responsible for speed control and heading. Three alternate airfields were available, all with different characteristics. Because of the dynamic nature of the exercise, the respective advantages of each destination changed as their positions relative to the aircraft changed.

The exercise ended when the crew' had either landed at a destination and taken the appropriate action (parked the aircraft or evacuated) or had decided to continue en route. The class then reconvened and each crew described, first, their actions and then explained their rationale. Each class comprised three sets of crew' and so it was possible to compare different performances. It was not uncommon to have three very different outcomes. Despite the low fidelity of the activity, it w'as still possible to see the effects of stress on performance and by having crew's comprising different ranks, it w'as possible to see the social dynamic at work.

The design concept illustrated in Figure 11.5 applies equally to a flight simulator or a desktop scenario. The low-fidelity approach allows for the exploration of competence while the high-fidelity device allows for the competence to be rehearsed under pressure. Effective training should exploit the strengths of available media according to the goal of the specific training intervention. Table 11.11 lists the different available media, together with their relative advantages.

In Chapter 1,1 said that training design typically starts w'ith a clear understanding of the desired performance outcome. A competence-based approach to CRM training is no different and, in this case, the outcome is performance defined by the competence model we have developed. We have seen that training is delivered in two different contexts: ab initio and in-service. In theory, the competence framework will be a constant but the range of operational contingencies to be managed by ab initio trainees is likely to be fairly limited. We may also decide that ab initio trainees should be exposed to more underpinning knowledge about CRM concepts. In-service training must fit crew's to cope with an escalating range of contexts. We can now' start to explore how different training media can be configured to support competence. There are two important questions that must be addressed from the outset: what level of fidelity is appropriate and does the activity need to be dynamic in terms of the role of time in accomplishing the task? Whereas fidelity may be important in terms of training transfer, for example in the case of aircraft manual

Desktop game. (Courtesy

FIGURE 11.7 Desktop game. (Courtesy: Captain Mark Sigson.)

handling, we have already seen that the simple visualisation of a task can still promote learning. Low fidelity actually removes complexity and allow trainees to focus better on the specific learning goal. I will limit this discussion to airline in-service training and I want to conclude this review of training methods by returning to the proposed list of candidate competencies developed in Table 11.6 and to see which of the approaches we have been considering might be used.

TABLE 11.11 Training Media

Media

Key Characteristics

Case studies and problem scenarios

Low cost, no dynamic properties, low' fidelity

Desktop exercise

Low cost, low fidelity, very flexible, gameplay can introduce dynamic dimension, able to run multiple crews simultaneously and compare performance

Tablet/iPad'1

Moderate cost, less flexible, requires IT support and investment in technology, can support group activity

Part-task trainer

Higher fidelity, allows systems management rehearsal, limited group size although some configurations allow for observers, limited scenario repertoire

Fixed-base trainer/simulator

Highest fidelity, can incorporate flight path control, systems management and malfunctions, group size limited, requires scenariobuilding skills

VR

High-fidelity, distributed, can involve multiple participants, requires investment and IT skills, reconfigurable

■ My thanks to Dr. Nick Dahlstrom at Emirates for information on the in-house development of this solution.

 
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