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This paper introduces a novel platform designed to optimize the formation of teams for hackathons and collaborative projects. The platform leverages a skill-based matching system, ensuring that users are paired based on their expertise and project requirements, fostering better team dynamics and performance. Key features include real-time notifications to keep users informed about ongoing hackathons, test results, and project milestones, alongside a mentorship module that connects participants with experienced mentors who guide them through the process. AI-driven algorithms are used to assess user competencies and match them to suitable teams, while the platform also includes a testing feature that evaluates compatibility and skill levels. Early findings suggest that the platform enhances user engagement, streamlines team-building processes, and improves overall project success. However, challenges related to fairness in team formation, as well as scalability issues with a growing user base, still need to be addressed. Looking toward the future, the paper outlines potential enhancements such as refining the fairness algorithms, integrating more advanced AI technologies for accurate matchmaking, and expanding features to improve team synergy and individual development. These advancements are expected to further elevate the platform's efficiency and user experience.
Keywords:
Team Formation, Skill-based Matching, Technology Assessment, Automated Team Matching, Project Optimization, Team Composition, Competency-based Teaming, Human Resource Management.
Cite Article:
"Hackomates: Revolutionizing Team Formation Through Skill-Based Test Matching", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c477-c481, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504280.pdf
Downloads:
000299
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator