Modeling student scheduling preferences in a computer-based testing facility
M. West and C. Zilles
in Proceedings of the Third ACM Conference on Learning @ Scale (L@S 2016), 309-312, 2016.
When undergraduate students are allowed to choose a time slot in which to take an exam from a large number of options (e.g., 40), the students exhibit strong preferences among the times. We found that students can be effectively modelled using constrained discrete choice theory to quantify these preferences from their observed behavior. The resulting models are suitable for load balancing when scheduling multiple concurrent exams and for capacity planning given a set schedule.
Full text: WeZi2016.pdf