Bello, K., & Aqlan, F., & Wood, D. (2024, June), A Utility-based Optimization Model for Allocating Student Teams to Community Projects  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/46507

\bibitem{asee_peer_46507}
  Bello, K., \& Aqlan, F., \& Wood, D. (2024, June), \emph{A Utility-based Optimization Model for Allocating Student Teams to Community Projects}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  https://peer.asee.org/46507

Khalid Bello, Faisal Aqlan, and Danielle Wood.  "A Utility-based Optimization Model for Allocating Student Teams to Community Projects".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/46507 Internet.  30 Jul, 2024

\bibitem{asee_peer_46507}
  Khalid Bello, Faisal Aqlan, and Danielle Wood.
  "A Utility-based Optimization Model for Allocating Student Teams to Community Projects".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/46507 Internet.  30 Jul, 2024

@INPROCEEDINGS{asee_peer_46507
author = "Khalid Bello, Faisal Aqlan, and Danielle Wood"
title = "A Utility-based Optimization Model for Allocating Student Teams to Community Projects"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/46507}
}

TY  - CPAPER
AB  - Participation in community-based projects provides students with invaluable benefits, including gaining practical experience and developing a sense of connection and belonging within the community. Nevertheless, the projects to which students are assigned can significantly influence their overall experience in this form of learning. Rather than relying on an approach that randomly assigns students to projects and often results in a mismatch between student preference and assigned project, we propose an optimization model to allocate community-based projects to students. The students provided a ranking of their project preference and 89 percent of all students received either their first or second choices. The optimization modeling approach not only streamlines the student-to-project allocation process for project coordinators but also ensures a consistent consideration of all relevant variables.
AU  - Khalid Bello
AU  - Faisal Aqlan
AU  - Danielle Wood
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - A Utility-based Optimization Model for Allocating Student Teams to Community Projects
UR  - https://peer.asee.org/46507
ER  -