Learning Tree is a system designed to visualize students’ learning journeys and skill development, transforming fragmented practice and answer data into a coherent, trackable learning path. Abstract learning progress is represented as a tree structure, allowing teachers to see where they are, what they’ve mastered, and what comes next. At the same time, it enables teachers to quickly identify learning gaps and understand overall class progress. In this project, I defined core use cases grounded in real educational contexts, structured information hierarchy and interaction logic, and balanced playfulness with pedagogical rigor so learning progress becomes more than just data, but a growth experience that is understandable and motivating.