Abstract: Embodiments of the disclosed systems and methods establish quantitative relationships between system features and system objectives. In some embodiments, the features have a plurality of feature values related to the objective and the methods comprise analyzing a mathematical functional relationship between the plurality of feature values and the objective to create a plurality of objective values reflecting the ability of the feature values to satisfy the objective, selecting a feature value and analyzing the relationship to create an objective value; and generating an objective measure reflecting the objective value. In some embodiments, the mathematical function comprises a polynomial interpolation. In some embodiments, the features are a fidelity dimension and the feature values are values of fidelity in a processor based aircraft simulator.

Abstract: Embodiments of the disclosed systems and methods establish quantitative and accurate relationships between system features and system objectives. In one embodiment, the systems and methods are particularly suitable to establish the predictive relationships between system fidelity and training objectives. These systems and methods can combine fidelity values defined by end-users, existing theory and research, or objective performance data from experiments. The predictive relationships defined through these methods can feed a model-based decision support tool that helps predict the impact of fidelity on training effectiveness.