PROJECT 04 / React Native prototype
LURN AI
Turn a learning goal into a path worth coming back to.
- Problem
- A broad learning goal needs an approachable starting point and manageable practice sessions.
- My contribution
- Directed guided course creation, mobile interaction design, visual style, and progress feedback with AI-assisted development.
- Working today
- A React Native / Expo prototype with 36 authored lessons, flashcards, practice, and local progress.
- Evidence
- The walkthrough shows learning paths and activities. Course content is prepared and the tutor is scripted; physical-device testing remains a next step.
A playful mobile learning prototype with personalized paths, practice, flashcards, and visible progress.
Challenge & context
Motivation needs a next step, not another content library.
A learning goal can feel too broad to start. LURN explores how an onboarding conversation, a clear path, and small practice sessions can help a learner move from intention to action.
- Start with the learner’s goal and available study time.
- Break a topic into lessons, practice, and milestones.
- Make weak areas and progress visible without overwhelming the learner.
My role & approach
Build the learning journey and the feeling together.
I directed a creation-first experience and a playful visual style through AI-assisted development. Raised purple buttons, rounded cards, a winding lesson path, and springy rewards give the interface energy while keeping the learning actions clear.
- Begin with an empty workspace and a guided course-creation interview.
- Keep touch controls large and important states easy to read.
- Respect reduced motion and preserve progress locally.
Solution & key workflows
Learn, practice, revisit, and see the progress.
The prototype includes authored Japanese, Python, and Meta Ads courses, each with lessons, tests, projects, and challenges. Flashcard scheduling, mastery evidence, and reinforcement branches connect the learning activities.
- Create a learning path and reveal its units and activities.
- Work through lessons and checks, then revisit concepts with flashcards.
- Use subject-specific practice labs and track goals, XP, and achievements.
Outcome & next steps
A mobile prototype with a real learning structure.
The app contains 36 authored lessons across three subjects and over 140 course recall cards. It exports iOS, Android, and web bundles. The tutor and course intelligence are local scripted behavior, not a live AI provider.
- Current state: a React Native / Expo prototype with local progress storage.
- Boundaries: no live speech assessment, arbitrary Python execution, cloud sync, or app-store release.
- Next: physical-device testing, accessibility testing, secure AI integration, and broader curriculum validation.
