Increasing Students' Engagement to Reminder Emails Through Multi-Armed Bandits. (arXiv:2208.05090v1 [cs.LG])

Conducting randomized experiments in education settings raises the question
of how we can use machine learning techniques to improve educational
interventions. Using Multi-Armed Bandits (MAB) algorithms like Thompson
Sampling (TS) in adaptive experiments can increase students' chances of
obtaining better outcomes by increasing the probability of assignment to the
most optimal condition (arm), even before an intervention completes. This is an
advantage over traditional A/B testing, which may allocate an equal number of
students to both optimal and non-optimal conditions. …

arxiv lg multi-armed bandits students