Community-based research (CBR) is a practice that engages researchers in collaborative, change-oriented, and inclusive projects in the community. One common example of CBR is university-community collaboration in which students and researchers come up with ideas, perspectives, and knowledge at each stage of the project with the goal to address community needs. The community is mainly involved in identifying the research questions for the projects and making decisions about how the results of the research-focused projects will be implemented. This paper presents a replication of a model focused on university-community collaboration, student engagement and Science, Technology, Engineering, and Math (STEM) attraction and retention using three research-focused projects addressing community needs. The three projects are (1) empathic design project aimed at improving quality greenspaces and pedestrian streetscape experience, (2) food justice project to study the disparities in food access between local regions, and (3) analyzing water quality in a local creek. The projects provided a unique opportunity for students to directly experience and contribute to the research process. In addition, students worked closely with their academic peers and community partners who served as collaborators and mentors. The study reports on the impact of the program on student learning and tendency to stay back in the community. The program's collaborative nature and its effect on students' satisfaction while working on specific projects are also examined. Furthermore, the program helped develop and sustain university-community partnerships. The community stakeholders participating in focus groups were satisfied with the process of identifying community projects and also expressed their satisfaction with the students’ work.
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A Utility-based Optimization Model for Allocating Student Teams to Community Projects
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.
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- Award ID(s):
- 2152282
- PAR ID:
- 10544628
- Publisher / Repository:
- 2024 ASEE Annual Conference & Exposition
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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