Assigning course schedules: About preference elicitation, fairness, and truthfulness

Martin Bichler, Sören Merting, Aykut Uzunoglu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Most organizations face distributed scheduling problems where private preferences of individuals matter. Course assignment is a widespread example arising in educational institutions and beyond. Often students have preferences for course schedules over the week. FirstComeFirstServed (FCFS) is the most widely used assignment rule in practice, but it is inefficient and unfair. Recent work on randomized matching suggests an alternative with attractive properties - Bundled Probabilistic Serial (BPS). A major challenge in BPS is that the mechanism requires the participants' preferences for exponentially many schedules. We describe a way to elicit preferences reducing the number of required parameters to a manageable set. We report results from field experiments, which allow us to analyze important empirical metrics of the assignments compared to FCFS. These metrics were central for the adoption of BPS at a major university. The overall system design yields an effective approach to solve daunting distributed scheduling tasks in organizations.

Original languageEnglish
Title of host publication40th International Conference on Information Systems, ICIS 2019
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683197
StatePublished - 2019
Event40th International Conference on Information Systems, ICIS 2019 - Munich, Germany
Duration: 15 Dec 201918 Dec 2019

Publication series

Name40th International Conference on Information Systems, ICIS 2019

Conference

Conference40th International Conference on Information Systems, ICIS 2019
Country/TerritoryGermany
CityMunich
Period15/12/1918/12/19

Keywords

  • Computational Social Science
  • Course Assignment
  • Field Study
  • Preference Elicitation

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