Proceedings of the Annual Meeting of the Cognitive Science Society

Working memory (WM) capacity is critically important for the success in school and complex cognitive activitiesacross the lifespan. Training WM skills has shown to lead to improvements in a variety of important cognitive tasks. One’sperformance on an adaptive and challenging longitudinal WM intervention may serve as an assay of cognitive plasticity. Withover 400 participants having completed a minimum of 15 sessions of WM training, we have a rich dataset that allows investigat-ing individual differences and other factors that might determine training outcome using a novel machine learning techniques.Preliminary results suggest that factors such as age, type of n-back, and baseline abilities significantly impact one’s ability toimprove in training. Other factors such as gender and whether or not training was supervised were not significant. Finally, ourmodel allows prediction of training gain with 78% accuracy.