2023 ASEE Annual Conference & Exposition

Work in Progress: An optimization model for assigning students to multidisciplinary teams by considering preferences and skills

Presented at Industrial Engineering Division (IND) Technical Session 2

Project-based learning has become popular and prevalent across higher education. Additionally, the Accrediting Board for Engineering and Technology also emphasizes the ability to function in multidisciplinary teams. These educational practices have resulted in the implementation of team-based projects throughout engineering curriculums. Team formation, however, is not a trivial process and occasionally can result in conflict or issues when completing project tasks. At our institution, we noticed that student interest level in a project topic/application is a significant factor toward commitment and contribution to project completion.

Our institution’s senior capstone requires students to participate in design projects where they are members of multidisciplinary teams solving open-ended real-world problems. Assigning students to projects can be a complicated process, especially considering student preferences, majors, skills, and the needs/nature of the project. We are a young program continuing to grow and are interested in a systematic approach to assign teams. Currently, a rank-based survey is used to gauge student interest in each individual project for assignment purposes. Faculty leaders consider students' ranking of the projects and the project needs to assign student teams. While we consider our current assignment method effective, it is a manual, time-intensive, and highly iterative process.

This paper presents a work-in-progress of a new assignment method using weight-based integer programming techniques. Some of the considerations for assignment weights and constraints include student preferences, student technical skill sets, team sizes, and faculty input. A comparative analysis between our proposed optimization model and the current assignment method is shown. Discussions of the similarities and differences between these two assignment methods are also presented.

Authors

Dr. Megan Hammond University of Indianapolis [biography]

Megan Hammond received her Ph.D. in Industrial Engineering from Western Michigan University. She is an assistant professor in the R.B. Annis School of Engineering at the University of Indianapolis. Her research interests include cluster analysis, anomaly detection, human centered design, and engineering education.
Dr. Joan Martinez http://orcid.org/0009-0002-9753-9346 University of Indianapolis [biography]

Joan Martinez is an assistant professor in the R.B. Annis School of Engineering at the University of Indianapolis. He received his Ph.D. in Industrial Engineering from Western Michigan University. His research interest lies in developing data-driven models within the fields of production systems, financial systems, decision sciences, and engineering education.
Dr. Joseph B. Herzog http://orcid.org/0000-0003-2441-6169 University of Indianapolis [biography]

Joseph B. Herzog is an Assistant professor in the R.B. Annis School of Engineering at the University of Indianapolis. He chose to come to the University of Indianapolis because he is passionate about teaching, is excited about the direction of the new R.B. Annis School of Engineering, is glad to return to his engineering roots, and is happy to be close to his extended family. Previously he was an Assistant Professor in the Department of Physics at the University of Arkansas. He is truly grateful for his time at the University of Arkansas, and enjoyed his department, students, and the campus. While in Fayetteville, he also served as a faculty in the Microelectronics-Photonics Program and the Institute for Nanoscience and Engineering. He received his PhD from the University of Notre Dame working in the Nano-Optics Research Lab with J. Merz and A. Mintairov. After this he was a Welch Postdoctoral Research Associate, researching plasmonic nanostructures at Rice University with Douglas Natelson in the Department of Physics &; Astronomy. In the summer of 2017 he was a Fellow at the U.S. Naval Research Laboratory (NRL) in Washington, DC working with Jake Fontana on tunable subnanometer gap plasmonic metasurfaces as part of the Office of Naval Research Summer Faculty Research Program. At the NRL he worked in the Center for Biomolecular Science and Engineering, which is a division of the Materials Directorate at the NRL. His experience also includes working for Intel Corporation both in Hillsboro, OR and Santa Clara, CA; and he worked at the Berliner Elektronenspeicherring-Gesellschaft für Synchrotronstrahlung m.b.H. (BESSY - Berlin electron storage ring company for synchrotron radiation) in Berlin, Germany, researching ultra thick high-aspect-ratio microfabrication. His research focuses on experimental nano-optics, including plasmonics, nanofabrication, computational modeling, photonic crystals, and engineering education.

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