Papers

Using Boolean Satisfiability Solvers to Help Reduce Cognitive Load and Improve Decision Making when Creating Common Academic Schedules

Joshua C. Manzano, Adrienne Francesca O. Soliven, Antonio Miguel B. Llamas, Shenn Margareth V. Tinsay, Briane Paul V. Samson & Rafael A. Cabredo

ACM CHI Conference on Human Factors in Computing Systems Proceedings (CHI), 2021 Acceptance Rate: 26%

Two interfaces of the prototype. The interface on the left allows users to compare schedules with other students while the one on the right allows the collaborative creation of schedule with friends.

Interfaces for comparing schedules with a friend and collaborative schedule generation with one or more friends.

Abstract

Manual schedule creation often involves satisfying numerous unique and conflicting constraints, which becomes more cognitively demanding when creating a common academic schedule with other individuals. Poor decision making caused by cognitive overload can result in unsuitable schedules. This study proposes the use of Boolean satisfiability (SAT) solvers in an academic scheduling system to help students balance scheduling preferences and satisfy necessary constraints. Based on the availability of courses and the scheduling preferences of users, the system automatically resolves conflicts and presents possible schedules. In a controlled experiment with 42 undergraduate students, cognitive demand was reduced by eliminating menial decisions, which significantly optimized the creation of a common schedule among peers. We found that human errors and emotional stress were diminished, and schedules created using the system were more satisfactory to participants. Finally, we present recommendations and design implications for future academic scheduling systems.

Materials

 Open Access ACM PDF  DOI

Bibtex

@inbook{manzano-sat-scheduler-2021, author = {Manzano, Joshua C. and Soliven, Adrienne Francesca O. and Llamas, Antonio Miguel B. and Tinsay, Shenn Margareth V. and Samson, Briane Paul V. and Cabredo, Rafael A.},
title = {Using Boolean Satisfiability Solvers to Help Reduce Cognitive Load and Improve Decision Making When Creating Common Academic Schedules},
year = {2021},
isbn = {9781450380966},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3411764.3445681},
booktitle = {Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems},
articleno = {456},
numpages = {13}
}

Citation

Joshua C. Manzano, Adrienne Francesca O. Soliven, Antonio Miguel B. Llamas, Shenn Margareth V. Tinsay, Briane Paul V. Samson, and Rafael A. Cabredo. 2021. Using Boolean Satisfiability Solvers to Help Reduce Cognitive Load and Improve Decision Making when Creating Common Academic Schedules. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 456, 1–13. DOI:https://doi.org/10.1145/3411764.3445681