Resource limitations make it hard to provide all students with one of the most effective educational interventions: personalized instruction. Reinforcement learning could be a key tool to reduce the development cost and improve the effectiveness of, intelligent tutoring software that aims to provide the right support, at the right time, to a student. Here we illustrate that deep reinforcement learning can be used to provide adaptive pedagogical support to students learning about the concept of volume in a narrative storyline software. Using explainable artificial intelligence tools, we also extracted interpretable insights about the pedagogical policy learned, and we demonstrate that the resulting policy had similar performance in a different student population. Most importantly, in both studies the reinforcement-learning narrative system had the largest benefit for those students with the lowest initial pretest scores, suggesting the opportunity for AI to adapt and provide support for those most in need.

本文介绍了利用深度强化学习提供个性化教育支持的方法，通过解释人工智能工具来提取可解释的教育策略。结果表明，该策略对于那些最需要支持的学生有最大的益处。

强化学习辅导在数学任务中更好地支持了表现较差者