Table 30: DUWIT Together

Inspiration

Hackathons unite innovators to explore the wonders of the coding realm, but nerve-wracking icebreakers often deter participation, especially for those with social anxiety. We realised there had to be a better way to form teams than the dreaded "Have you found a team yet?" questions. With this realisation, the idea for DUWITTogether was born. This platform uses AI to analyse skills, personalities, and interest areas, creating more compatible and productive teams, to optimise every participants' potential during their time at Hackathons. Our aim is to enhance team-building and make hackathons a more positive, collaborative experience where everyone can contribute effectively with an 'ideal' team dynamic.

What it does

This platform helps users find their ideal hackathon team by allowing them to showcase their skills, interests, experience level, and traits. It then generates 10 AI-driven questions to refine their preferences, assessing key personality traits such as willingness to learn, collaboration style, focus level, leadership tendencies (sheep or wolf), ingenuity, determination, patience, communication style, and thinking approach (detail-oriented or conceptual). Based on their responses, the platform provides a final result, ensuring better team compatibility and performance.

How we built it

First, we researched the key factors to consider when evaluating a person’s personality type. We then allocated roles based on our strengths: one person worked on AI, another focused on User Interface (UI) and the implementation of UI/UX, another handled design, and the last person took charge of the database, framework, and deployment.

Challenges we ran into

Different experiences in our past exposure of coding, leading to different skillsets. With different coding experiences can make collaboration due to varying expertise levels. In this project, we had to implement JavaScript and was very different from what we have learnt before. Remembering the correct order of code execution was crucial, adding another layer of complexity. To add on, every group member was taking on different tasks while building the website, making it challenging to integrate our individual contributions into a cohesive final product.

Accomplishments that we're proud of

Despite our differences, we successfully developed a platform that met our main goal, which is creating personality quizzes that consider collaborative styles in team settings. We remained understanding of each other's expertise levels and made the most of our combined skills to finalise our product.

What we learned

We expanded our coding skills by learning JavaScript, Figma, and React. We also gained experience in integrating APIs into our website. Most importantly, we learned how to collaborate effectively and leverage each other's strengths to bring our project to life.

What's next for A website

The platform will focus on matching user profiles based on their skills, experience, and personality traits. Using AI-driven analysis, it will create well-balanced teams with complementary strengths, optimising collaboration and users' performance in hackathons.