Extending the TNA process: an innovative approach to training analysis using data-rich hierarchy mapping

Many training analysis systems have tended to focus on identifying task components and their relationships with each other, in order to develop training objectives. The approach outlined concentrates its efforts on identifying human performance and interaction between task components, exploiting modern thinking where the user is the center of the system. This is especially true of modern training systems. Initially, the methodology appears to the user to be a simple task hierarchy, and indeed the first element of conducting an analysis with this methodology is to identify and sequence all the task elements. This innovative approach assesses the cardinal parameters of criticality, complexity, and novelty. The methodology also utilises previous (internal) research into domain mapping to provide the analyst with tools for mapping each defined element into a `technology matrix´. This approach gives rise to a large amount of data. Our approach has been to create a specific data manipulation tool for the creation and integration of training objectives, task and user data through a series of generic forms that categorise the training data. From this solid information base, the training analyst has the ability to create `what if. . .´ scenarios for data extraction, to build comprehensive data dictionaries, and to produce a wide variety of analytical and informational reports. The paper is illustrated by drawing on training studies undertaken by Marconi Simulation