No abstract

C ourse assignment is a very widespread problem in education and beyond. Typically, students have preferences for bundles of course seats or course schedules over the week, but courses have limited capacity. This is an interesting and frequent application of distributed scheduling, where payments cannot be used to implement the efficient allocation. First-Come First-Served (FCFS) is simple and the most widely used assignment rule in practice, but it leads to inefficient outcomes and envy in the allocation. It was recently shown that randomized economic mechanisms that do not require monetary transfers can have attractive economic and computational properties, which were considered incompatible for deterministic alternatives. We use a mixed-methods design including field and laboratory experiments, a survey, and simulations to analyze such randomized mechanisms empirically. Implementing randomized scheduling in the field also required us to develop a solution to a new preference elicitation problem that is central to these mechanisms. The results of our empirical work shed light on the advantages that randomized scheduling mechanisms have over FCFS in the field, but also on the challenges. The resulting course assignment system was adopted permanently and is now used to solve course assignment problems with more than 1700 students every year.