UX Research & Design
AEye
Human-Computer Interaction Final Project
AEye is a mobile learning concept that helps users distinguish AI-generated content from real-world media through educational modules and repeat-use game loops.
My contribution
- Conducted user interviews to uncover misconceptions and learning friction.
- Synthesized findings into personas and structured journeys.
- Designed core learning flows, feedback loops, and social features.
- Led usability iterations to improve discoverability and navigation clarity.
The outcome
Improved navigation clarity and feature discoverability across learning and social flows, demonstrating end-to-end UX ownership from research to prototype delivery.
Behind the work Research, process & screens
The challenge
- AI literacy tools are often too technical or not engaging enough for repeat use.
- Users need low-friction practice that reinforces pattern recognition over time.
- Feature discoverability and action hierarchy can break learning momentum.
The approach
- Designed daily challenge loops for habit formation.
- Added progression systems with points, levels, and milestones.
- Used local and global leaderboards to reinforce motivation.
- Repositioned social actions after discoverability testing feedback.
