Abstract or Table of Contents
A theory of prospective time perception is presented that extends existing theories by incorporating it as a module in an integrated theory of cognition, allowing predictions about attention and learning. First, a time perception module is established by fitting existing datasets (interval estimation, bisection and impact of secondary tasks on attention). The module is subsequently used as a part of the ACT-R architecture to model a new experiment that combines attention, learning, dual tasking and time perception. Finally, the model predicts learning and attention in a new experiment. The model fits and predictions demonstrate that the proposed integrated theory of prospective time interval estimation explains detailed effects of attention and learning during time interval estimation.