Students Unite!

Inspiration

The idea for the AI Study Group Matchmaker was inspired by the challenges many students face in finding study partners who share their interests and work habits. In addition, students often struggle with choosing the right professor, which can significantly impact their academic success. I wanted to create a tool that not only connects like-minded students but also provides AI-based professor recommendations for an optimized learning experience.

What it does

The platform connects students based on shared study habits, interests, and courses, creating a personalized study group match. It also integrates with an AI-powered feature that offers professor recommendations, helping students find professors who best match their learning style.

How I built it

I built the project using a combination of machine learning models for interest and habit matching, and natural language processing (NLP) for professor recommendations. The frontend was created with React, while the backend integrates AI models via Node.js and Express.js. I also incorporated APIs like OpenAI to gather professor ratings and reviews.

Challenges I ran into

One of the biggest challenges I've faced was trying to finish the project on my own, as my teammates left and joined other teams. So the end result is very unpolished, looks and functions are incomplete as it was genuinely hard to complete the ambitious vision I had alone, and with a time constraint adding on to it.

Accomplishments that I'm proud of

I'm proud of even trying to create a platform that not only connects students but also leverages AI to provide valuable insights on professor selection, but it wasn't enough.

What I learned

Through this project, I learned the importance of user-centric design, especially when building tools for students. I also gained deeper insight into AI-based recommendation systems, their potential, and the ethical considerations surrounding their use in academic settings. Finally, I learned how to integrate multiple technologies into one cohesive platform, managing both the technical and UX aspects.

What's next for Students Unite!

In the future, I do plan on expanding the potential that the AI Study Group Matchmaker is capable of by incorporating more personalized features, such as study session scheduling, resources links and task management tools. I also aim to enhance the professor recommendation feature by collecting more comprehensive data on teaching styles and class structures. Another goal is to implement better data analytics to continuously improve our matching algorithms and deliver a more tailored experience to students.

Built With

• express.js
• firebase
• next.js
• openai
• react