In this study we manipulated how frequently different problems were practiced during a first day of practice, with the more frequent items being more closely spaced. Fitting the data to a skill acquisition model, we find that greater spacing between items is associated with an increased probability of transitioning to more efficient phases of performance, but with a shallower speedup within each phase. Three days after training, we find that performance is predicted not by the practice frequency during training, but rather by the phase of skill acquisition attained during training. Thus, it is type of processing achieved not the amount and spacing of practice, that determines retention. Spacing, however, promotes learning by driving changes in cognitive processing.

Collins, M., Tenison, C., Gluck, K., & Anderson, J. (2020). Detecting Learning Phases to Improve Performance Prediction. The 18th Annual Meeting of the International Conference on Cogntive Modeling.(Paper available here)

Tenison, C., & Anderson, J. (2017). The Impact of practice frequency on learning and retention. The 39th Annual Meeting of the Cognitive Science Society .(Paper available here)