🤖 AI Summary
This study addresses the multi-stage coordination challenges in managing capstone course projects at higher education institutions, particularly concerning student interest alignment, external project solicitation, and team formation. The authors propose and implement a web-based management platform designed to facilitate academic–industry collaboration, marking the first application of a systematic digital tool across the entire capstone project lifecycle. The platform emphasizes automated project solicitation and algorithm-driven intelligent team formation, integrating student profiles, project data, and matching logic to support multi-stakeholder collaboration. Deployed successfully at Insper, the system has significantly improved both the efficiency of project allocation and the quality of team composition, offering a reproducible operational model and foundational dataset for similar educational contexts.
📝 Abstract
Capstone projects are widely adopted by universities around the world as a culminating assessment in bachelor's degree programs. These projects typically involve student teams tackling complex, real-world problems proposed by external stakeholders, such as companies, NGOs, or research centers. Although they offer valuable hands-on experience, managing Capstone projects can be challenging due to their multiple stages and demands. The process typically begins by identifying students' interests, followed by sourcing and selecting potential projects from external organizations. After presenting these options to students, groups must be formed based on various criteria, including academic ranking, GPA, previous experience, and individual skill sets.
In this paper, we detail a web-based tool designed to streamline the management of Capstone projects at Insper, with an emphasis on project sourcing and group formation. We also discuss the technological solutions and the challenges encountered throughout development and deployment. Furthermore, we present usage data from recent years, offering insights that may prove valuable for institutions or teams developing similar tools in the future.