Large scale training exercises involve many trainees at various stages of their training maturity and at various levels of skill. Problems arise in large scale exercises when less mature or lower skilled trainees are exposed to training scenarios that are too advanced or too complex for their level of training maturity. These trainees are more likely to fail the mission they are given in the training scenario, thus reducing the benefits of training and leading to frustration in the trainee. We propose to develop a tool called SKATE (Skill Appropriate Training Environment) that will quantify skill levels of trainees, teams, or units, generate skill appropriate training objectives, modulate the difficulty of training scenarios, and provide a continuous skill-level assessment and scenario adaptation of disparately skilled trainees, teams, and units in a large scale training exercise while maintaining the overall integrity and realism of the mission itself. SKATE will evaluate the skill level of an individual, team, or unit level participants and generate a list of skill-appropriate training scenario components that can be configured into the exercise so as to fulfill the training objectives of the participants. SKATE will be designed on the basis of relational data-mining technology.
Benefit: The goal of SKATE is to improve the quality of training while at the same time reducing cost by reducing frustration in novice participants and boredom in expert participants. SKATE will accomplish this by assessing the skill-level of trainees, teams, or units and by generating skill appropriate training objectives that will ensure that the trainees will not be subjected to training scenarios that are well over their heads and that would lead to mission failure. We are confident that future network centric training systems will be practically indistinguishable from their fighting counterparts. In fact, we think that they may be the same systems, in that computerized crew station technologies used on ships, in aircraft, vehicles, and the electronic gear used by dismounted warfighters will be used to train and fight without configuration changes. Computerized weapons systems can concurrently serve as training simulators and as fighting systems. With this fight as we train 0x9D concept in mind, we feel that all simulated and real mission activities performed by our warfighters should be graded and assessed with tools such as SKATE. Based on this philosophy, we configured our SKATE concept such that continuous assessment of performance and skill can be accomplished regardless of whether the mission is simulated or real.
Keywords: Skill-appropriate training objectives, Skill-appropriate training objectives, performance variables, relational data mining, Navy Standard Score (NSS)
