The Quest Draft: an Automated Course Allocation Algorithm
Year: 2014
Type: conference-paper
Abstract: Course allocation is one of the most complex issues facing any university, due to the sensitive nature of deciding which subset of students should be granted seats in highly-popular (market-scarce) courses. In recent years, researchers have proposed numerous solutions, using techniques in integer programming, combinatorial auction design, and matching theory. In this paper, we present a four-part AI-based course allocation algorithm that was conceived by an undergraduate student, and recently implemented at a small Canadian liberal arts university. This new allocation process, which builds upon the Harvard Business School Draft, has received overwhelming support from students and faculty for its transparency, impartiality, and effectiveness.
Authors: Richard Hoshino, Caleb Raible-Clark
Institution: Quest University Canada
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W132575962