Final Project Idea
31 Mar 2026
Overview
The Problem
UH Mānoa students face difficulty every semester when choosing classes. Tools like RateMyProfessors are often too general or overly negative, and official UH systems provide little insight into real difficulty, workload, teaching style, or the best time to take a course. This leads to poor scheduling decisions, unexpected stress, and lower academic performance.
The Solution
Mānoa CourseWise is a Next.js web application built with React and Bootstrap 5 that lets UH Mānoa students share and discover honest, constructive reviews of courses, professors, and TAs. The app includes searchable course pages, schedule conflict checking, crowd-sourced “best semester” stats, and warning flags for common issues.
Names of the Proposers
- Noah Nguyen
- Ryan Stuckey
- Jaymond Guan
- John Crabtree
Mockup Page Ideas
- Home/Landing Page: Hero banner with UH Mānoa branding, prominent search bar, and featured courses.
- Course Search Page: Filterable grid showing courses with average ratings, difficulty, and workload.
- Course Detail Page: Reviews list, statistics, constructive flags, and built-in schedule conflict checker.
- Submit Review Page: Form for logged-in users with ratings, sliders, and flag selection.
- User Dashboard: Personalized recommendations, my reviews, and saved courses (the “special sauce”).
All pages will be fully responsive using Bootstrap 5.
Use Case Ideas
- A student searches for “ICS 311” and quickly sees average difficulty, workload, and helpful student flags.
- After logging in, a user submits a review for a class they just finished and receives personalized course suggestions based on their major and past ratings.
- A student adds several courses to a planner and instantly sees time conflicts with alternatives suggested.
- Users can mark helpful reviews, helping the community over time.
Beyond the Basics
The special sauce is the personalized user experience after registration and login. Each user has their own profile (major, year, learning preferences) that affects recommendations and highlights reviews from similar students. Each course and each professor could also have tags used to provide recommendations for specific courses. Data is stored persistently, so the app feels unique to every logged-in user.
Use of AI: Grammarly was used to correct mistakes in grammar to make ideas more clear. Grok was also used to help suggest how to format parts of the markdown (adding bulllet points, bold lettering, etc).