High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)

Abstract

Increasing student populations and diverse course offerings have led to perceived inequities in U.S. high school course scheduling. Traditional integer programming (IP) methods for the High School Scheduling Problem (HSSP) fail to address these fairness concerns. This research introduces the Fair High School Scheduling Problem (FHSSP), an extension of the HSSP that incorporates student preferences and fairness principles from market design. We develop an IP model to generate course schedules that are both feasible and equitable. Tested on real course request data from a California high school, our model successfully produces schedules that ensure fairness without compromising feasibility. These results demonstrate the potential of our approach to enhance fairness in high school scheduling and its applicability to various real-world scheduling challenges. Additionally, this study highlights the feasibility of integrating human preferences and emotions into mathematical models, promoting more inclusive and balanced allocation systems.

Cite

Text

Kiyohara. "High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35265

Markdown

[Kiyohara. "High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/kiyohara2025aaai-high/) doi:10.1609/AAAI.V39I28.35265

BibTeX

@inproceedings{kiyohara2025aaai-high,
  title     = {{High School Course Scheduling: Student Preferences and Fairness Constraints (Student Abstract)}},
  author    = {Kiyohara, Mitsuka},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {29399-29400},
  doi       = {10.1609/AAAI.V39I28.35265},
  url       = {https://mlanthology.org/aaai/2025/kiyohara2025aaai-high/}
}