Reinforcement learning for the adaptive scheduling of educational activities

We show that a Reinforcement Learning (RL) model produces better learning gains using fewer educational activities than a linear assignment condition, and produces similar learning gains to a self-directed condition using fewer educational activities and with lower dropout rates.