StuddyBuddy

Inspiration

The goal of the university is to produce knowledgeable students. That is tested through assessments. After these assignments are graded, the students are not motivated to improve their mistakes in these assessments.

What it does

Our app gives students a second chance to redo the sections where they missed marks and submit a makeup assignment to upgrade their grade by a certain percentage. This results to improve academic performance by offering personalized opportunities for students to focus on their weak area.

How we built it

Prototype on Figma, front-end on Swift-UI, back-end on FastAPI, code bases are on git-repos.

Challenges we ran into

Our goal was to use LLM integrations to produce the personalized recommendations with the use of mock data but ran into time constraints. Hence we ended up giving a proto type to give the idea behind what our end goal is.

Accomplishments that we're proud of

The Solution we are giving is pretty impressive and quite apt for students and their expereinces at University. Although we were'nt able to finsh integrating the back-ends with the UIs, with the time we were able to contribute we built stand alone features for UI, front-end and a little bit of back-end.

What we learned

Working with tight timelines and comeup with alternatives for the solution. Some of us were new to product development so had plenty to learn from.

What's next for StuddyBuddy

Build the recommender systems with connecting to relevent data-sources Improve the FE and BE and integrate them, finalize the product.

Built With

• fastapi
• figma
• openai
• python
• swiftui