Automated decision-making is becoming increasingly common in the public sector. As a result, political institutions recommend the presence of humans in these decision-making processes as a safeguard against potentially erroneous or biased algorithmic decisions. However, the scientific literature on human-in-the-loop performance is not conclusive…

Contextual multi-armed bandits have previously been used to personalize student support messages given to learners by supplying a model with relevant context about the user, problem, and available student supports. In this work, we propose using careful feature selection with relevant domain knowledge to improve the quality of student support…