This work presents a web application created to help instructors assign students to group projects, with an algorithm that optimizes student satisfaction, gives students the opportunity to select a team member, and reduces time needed for an instructor to create teams. Our approach focuses on two main aspects: (a) it gives the student the ability to apply weights to their project choices (instead of just ranking them) and (b) it provides students with the opportunity to select a classmate to be partnered with. We implemented a genetic algorithm 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.
|ASEE Annual Conference and Exposition, Conference Proceedings
|Published - Jun 22 2020
|2020 ASEE Virtual Annual Conference, ASEE 2020 - Virtual, Online
Duration: Jun 22 2020 → Jun 26 2020
ASJC Scopus subject areas
- General Engineering