Proceedings of the Annual Meeting of the Cognitive Science Society

This research investigates the impact of time pressure and individual differences on learning in a Real-Time Dynamic Decision Making (RTDDM) task. Our empirical results indicate that high time pressure generates high cognitive loads inhibiting learning. The results also show that high time pressure have a differential impact on the learning of individuals with high or low Working Memory (WM) capacity. W e present a cognitive model based on ACT-R intended to explain learning in tiiis task. Our cognitive model simulates learning by recognizing regularities in the decision task, and building "chunks" that guide decision making (instance-based learning). We describe how the model will be used to explain the impact of time pressure and WM capacity by varying the number of chunks acquired by the system given alternative time pressure conditions and individual differences.