Virtual On line
June 22, 2020
June 22, 2020
June 26, 2021
Design in Engineering Education
This work presents a web application created to help instructors assign students to group projects, with an approach that optimizes student satisfaction, gives students the opportunity to select a team member, and reduces the instructor time creating the teams. Previous work that analyzed data from senior capstone teams indicate that team composition is one of the most important factors that contribute to student satisfaction , and for that reason many authors have proposed methods to better distribute students in teams corresponding to predetermined projects [2–4]. Our approach focuses on three main aspects: (a) it gives the student the ability to apply weights to their project choices (instead of just ranking them), (b) it provides students with the opportunity to select a classmate to be partnered with, and (c) it creates an open-source web-based tool that can be used by others.
Our tool consists of an implementation of a genetic algorithm (GA) that assigns students to projects in order to maximize the fitness function, defined as a multi-objective function to increase student satisfaction, decrease the variance of team sizes, and optionally decrease the GPA variance among team members. To achieve this, students view a list of available projects and must allocate “points” across a minimum number of projects based on their personal interest in the project. For example, in one course students assigned 15 points across a minimum of 6 projects. In addition to the individual points, instructors can require certain student-project assignments and instructors can allow students to allocate their points as a team to ensure they are on the same project.
This GA tool has been used by instructors of the capstone design course in a mechanical engineering program for over 5 years, impacting more than 1100 students. Instructors reported that the previous process of manually creating the teams involved a total of 1–2 days of work, and that they are now able to assign all of the students to project teams in less than two hours. Students are no longer assigned to projects that they did not select, and about 80% of the students are assigned to projects they had given a high weight. In surveys, students report they are highly satisfied with their team and project assignments at both the beginning of the semester and after the semester. Indeed, the distribution of student satisfaction with their team assignment becomes even more positive upon completion of the course. Students also indicate informally that they appreciate being able to select one classmate to be part of their team.
 Bosco et al (2009): “The effect of team selection method on the occurrence and nature of conflict”, Journal of Applied Research for Business Instructions, vol 7(1), 2009.  Michaelis, B. and Bae, H. (2019): “Optimizing Capstone Team Selection”, ASEE 2019.  Freiheit, T. and Wood J. (2007): “An algorithm for project assignment in capstone design”, ASEE 2007  Schmidt et al. (2011): “An optimized routine for assigning students to capstone project groups”, ASEE 2011.
Mohan, A. K., & Dey, P., & Tan, S., & Johnson, B. E., & Fagen-Ulmschneider, W., & Silva, M. (2020, June), Introducing junto: a Web Tool to Build Project Teams based on a Bidding Strategy Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34876
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