The utilization of reinforcement learning (RL) within the field of education holds the potential
to bring about a significant shift in the way students approach and engage with learning and …

This survey article has grown out of the RL4ED workshop organized by the authors at the
Educational Data Mining (EDM) 2021 conference. We organized this workshop as part of a …

As bandit algorithms are increasingly utilized in scientific studies and industrial applications,
there is an associated increasing need for reliable inference methods based on the resulting …

Bandit algorithms are increasingly used in real-world sequential decision-making problems.
Associated with this is an increased desire to be able to use the resulting datasets to answer …

Simulation is a powerful approach that plays a significant role in science and technology.
Computational models that simulate learner interactions and data hold great promise for …

Bandit learning has been an increasingly popular design choice for recommender system.
Despite the strong interest in bandit learning from the community, there remains multiple …

Advances in artificial intelligence (AI) and machine learning can be leveraged to tailor
training based on the goals, learning needs, and preferences of learners. A key component …

How can educational platforms be instrumented to accelerate the use of research to improve
students' experiences? We show how modular components of any educational interface-eg …

Personalized learning stems from the idea that students benefit from instructional material
tailored to their needs. Many online learning platforms purport to implement some form of …

Using bandit algorithms to conduct adaptive randomised experiments can minimise regret,
but it poses major challenges for statistical inference (eg, biased estimators, inflated type-I …