Smart Team Builder for College Hackathons: A Comprehensive Survey

Abstract

Hackathons have emerged as high-intensity, innovation-driven events that foster collabora- tion among students to solve real-world problems in limited timeframes. The success of such events largely depends on team composition, as balanced and diverse teams enhance creativity, efficiency, and overall performance. However, traditional team formation methods, including random allocation or self-selection, often result in imbalanced skill distribution, interpersonal conflicts, and underutilization of talent. The proposed system, Smart Team Builder for Col- lege Hackathons, leverages artificial intelligence, optimization techniques, and social network analysis to automate the formation of well-balanced and compatible teams. By integrating par- ticipant skills, experience, interests, and personality traits, the system ensures diversity, fairness, and optimal skill coverage. Cloud-based storage and real-time analytics dashboards provide or- ganizers with detailed insights into team composition, workload balance, potential conflicts, and collaboration effectiveness. Furthermore, the system supports dynamic reallocation in re- sponse to participant dropouts or late registrations, while incorporating fairness constraints to promote gender and academic diversity. This survey paper reviews prior work in team formation for hackathons, collaborative learning, and organizational settings, identifies key limitations in existing approaches, and proposes a comprehensive Smart Team Builder framework aimed at maximizing hackathon outcomes, improving participant engagement, and reducing administra- tive workload.