Embedded Files
High-Fidelity Prototype: User Profile Page
Our app addresses the fragmented course planning experience by consolidating peer insights, UW data, and AI-powered guidance into a single platform. The design centers around two key features: an AI scheduling chatbot and a student-driven course review system.
Upon logging in with their UW credentials, new users are prompted to enter context about themselves including work hours, clubs, and extracurriculars. AI can then use this information to generate personalized course recommendations. The front page lands directly on the AI chat, where students can ask questions like "What classes should I take next quarter?" or "What requirements do I still have before I can graduate?" Because the AI draws on the user's actual profile data and the rating and reviews system, its answers go beyond generic suggestions and account for each student's real workload and commitments.
Low-Fidelity Prototype
High-Fidelity Prototype: Figma Design Flow
From the main screen, users can navigate to four core areas: the AI chat, course search, past reviews, and add a review. The course search lets students look up any UW course and see peer-submitted ratings including difficulty and whether students would recommend it. Users can also submit their own reviews for courses they've taken, creating a growing, student-sourced database that gets more useful over time.
User Flow Diagram
The user flow, shown above, maps the full interaction from login through each feature, illustrating how the app routes returning versus new users and how the navigation system connects all features without requiring repeated back-button use, a friction point identified directly from usability testing.
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