Inspiration
As students, we know the experience of looking for clubs we would be interested in, and forgetting events, clubs meetings, and other opportunities.
What it does
CampusConnect is a student engagement platform that helps users discover, rank, and manage campus events. It allows students to browse upcoming university events, complete personalized questionnaires to get tailored recommendations, and easily add selected events to their Google Calendar.
How we built it
CampusConnect was built using Python and Streamlit for the frontend interface, creating an interactive and responsive web app. We used JSON to store and manage event data, allowing users to rank and personalize their recommendations. Additional Python modules handled features like dynamic event filtering, calendar integration, and user questionnaires. The app was developed in a virtual environment for easy dependency management and deployment.
Challenges we ran into
We ran into issues setting up our Python environment on macOS, especially with installing Streamlit and PyArrow due to system restrictions. Managing multiple Streamlit pages, fixing duplicate element errors, and correctly handling event data and ranking logic also required careful debugging and testing.
Accomplishments that we're proud of
This was our first time building a web app, and while it’s not yet the full version we envisioned, we’re proud to have designed and deployed a functional prototype from scratch! We successfully created an interactive user interface and implemented an algorithm that generates personalized event recommendations — a huge milestone for our first development project.
What we learned
Through building Campus Connect, we learned the fundamentals of full-stack development — from structuring a multi-page Streamlit web app to connecting scripts for different functionalities. We gained hands-on experience with environment setup, virtual environments, and troubleshooting complex installation issues like pyarrow and CMake errors. We also deepened our understanding of user-centered design by creating an interactive onboarding questionnaire and developed a recommendation algorithm that ranks events based on user preferences and tags.
What's next for Campus Connect
Currently, event recommendations are generated manually by entering each event and its associated tags. In the future, we plan to integrate AI to automatically pull event and club data from campus sources and generate tags dynamically. We also aim to improve our recommendation system by shifting from a simple ranking (1–12) to a personalized match percentage based on user preferences. Beyond events, we want to include club recommendations to help students find long-term communities on campus. Lastly, we plan to implement key features like user authentication and saved events, so every student can have a personalized dashboard tailored to their campus experience.
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