GMU BICA is a biologically inspired cognitive architecture developed at George Mason University. Its main distinguishing feature is a system of data structures called “mental states” that enables various forms of metacognition. The present study develops an understanding of the role of metacognition during working scenario generation (a general element of the cognitive cycle in GMU BICA). This is done by a computational experiment with a rapid prototype of the architecture that generates metacognitive mental states. A spatial learning / spatial navigation paradigm is used here, with a virtual robot implemented in CASTLE. Results show a significant increase in both behavioral and cognitive efficiency of the agent when metacognition is turned on. Generalizations are discussed.