Project Info
Inspiration
Our inspiration for this project came from a quote by a UCSC student: “My regret is not being more involved in campus activities, clubs, etc. Do well in your classes, but also let yourself have fun and try new things.” One major barrier to an engaging and fulfilling college experience is the lack of involvement a student might have in clubs. This often stems from the difficulty of finding organizations that genuinely align with a student’s interests and finding the correct club from a sea of information. UCSC Activity Finder was created to address this problem. What It Does UCSC Activity Finder provides users with a short questionnaire that identifies their interests and matches them with relevant campus clubs. Based on the quiz results, the extension generates a curated list of clubs along with their contact information and descriptions. Users can explore this refined list to find activities that suit them or “roll the dice” to discover a random club to join. By centralizing all campus clubs in one place and narrowing them into manageable lists, the extension makes student involvement more accessible and less overwhelming. How We Built It We initially used Python to prototype and test the core logic of the system. Once the main functions were working, we transitioned the codebase to JavaScript and HTML for the Chrome extension. Club data and associated tags were stored in a JSON file, which was generated beforehand using Python. HTML was used to structure the extension’s layout, while JavaScript handled the application logic and interactivity. We also used Canva to design the visual elements and overall layout of the extension. Challenges We Ran Into One of the main challenges was determining which questions to ask and how to structure them to minimize time spent on answering. We spent a significant amount of time refining the questionnaire to accurately capture user interests while keeping it concise. The biggest challenge, however, was formatting the extension itself. Aligning buttons, text, and overflow behavior with our Canva mock-ups proved difficult, and resolving these layout issues took the better part of Saturday. Accomplishments That We’re Proud Of This was our team’s first hackathon, and we were proud to complete a functional project from start to finish. As high school students, it was especially fun to compete alongside college students. Another major accomplishment was having our base product completed by the end of the Friday. What We Learned Through this project, we learned how sensitive HTML layouts can be when combined with JavaScript behavior. We also gained valuable experience in organizing, storing, and efficiently searching through large datasets. What’s Next for UCSC Activity Finder We will focus on perfecting our extension. Once we have done some testing with UCSC students and improved our searching algorithm, we will expand to other colleges. We can also improve user experience.
Analysis
View
Metric
- 15
- 6
- 1
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- HTMLIn code
- JavaScriptIn code
- PythonIn code
3 of 3 appear in the indexed code.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
30 KB
Source files
8
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
BasiCubes950/cruzhack-yippie
17 files · 1.8 MB · @ 63d566d
Structure
Interface
2 files · 12%Screens, components and styles rendered to the user.
Application logic
8 files · 47%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- JavaScript60%
- Python25%
- HTML15%
- Markdown1%
Share of indexed source by file size. Binary and vendored files are excluded.
This project’s features have not been analysed yet.
Export this project's context (description, README, evidence, key source files) to chat with an AI agent elsewhere.