Towards precise measures of individual performance in complex tasks

Simple laboratory tasks typically allow one or a few methods of task performance. In contrast, moderately complex tasks, such as video games, provide many methods of task performance which, in essence, provide many ways of completing the task without necessarily completing all possible components. Although performance on complex tasks improves with practice, the improvements do not represent the simple effects of power-law learning but, rather, they tend to reflect the discovery and practice of a diverse set of methods. Understanding what we see during complex task learning, requires us to evaluate individual performance against benchmarks of optimality. In this report, we use the game of Space Fortress (SF) as a complex experimental paradigm in which we demonstrate two alternative measures that reveal scopes of individual differences in the discovery and implementation of an optimal method that would be missed by traditional measures of the game.