Methods and Tools in Computer-Supported Taskforce Training


Johan Jenvald


Efficient training methods are important for establishing, maintaining and developing taskforces that are organised to manage complex and dangerous situations in order to serve and protect our society. Furthermore, the technical sophistication of various systems in these organisations, for example command, control and communication systems is growing, while the resources available for training are being reduced due to budget cuts and environmental restrictions. Realism in the training situation is important so that the actual training prepares the trainees for, and improves the performance in, real situations. The ability to observe and review the training course of events is crucial if we want to identify the strength and shortcomings of the trained unit, in the overall effort to improve taskforce performance.
This thesis describes and characterises methods and tools in computer-supported training of multiple teams organised in taskforces, which carry out complex and time-critical missions in hazardous environments. We present a framework that consists of a training methodology together with a system architecture for an instrumentation system which can provide different levels of computer support during the different training phases. In addition, we use two case studies to describe the application of our methods and tools in the military force-on-force battle-training domain and the emergency management and response domain.

Our approach is to use an observable realistic training environment to improve the training of teams and taskforces. There are three major factors in our approach to taskforce training that provide the necessary realism and the ability to make unbiased observations of the training situations. The first factor is the modelling and simulation of systems and factors that have a decisive effect on the training situation and that contribute in creating a realistic training environment. The second factor is the data collection that supports unbiased recording of the activities of the trained taskforce when solving a relevant task. The data are received both from technical systems and from reports based on manual observations. The third factor is the visualisation of compiled exercise data that provides participants and others with a coherent view of the exercise.

The main contribution of this thesis is the systematic description of the combination of a training methodology and a system architecture for an instrumentation system for computer-supported taskforce training. The description characterises the properties and features of our computer-supported taskforce-training approach, applied in two domains.