2025 · BSc thesis · full-stack · ML
EloQuiz.dk
Adaptive math learning platform that uses an Elo-based difficulty system to match each student to the right next question.
- Vue
- Flask
- Firebase
- OpenAI API
Overview
EloQuiz.dk is an adaptive math learning platform built around an Elo-rating system: every student and every question has a rating, and the matchmaking loop tries to keep students at the productive edge of their ability.
This started as my BSc thesis on adaptive learning systems and grew into a real product validated through a student pilot.
What I built
- A full-stack web app (Vue front-end, Flask back-end, Firebase for auth and data) deployed end-to-end.
- The Elo-based difficulty engine: students and items co-rate each other, letting the system surface problems in a student’s zone of proximal development without manual curriculum tagging.
- LLM-assisted question generation and explanation flows powered by the OpenAI API.
What I learned
How brittle a “smart” model gets the moment real students start using it. Most of the engineering work was the loop around the model: onboarding, explanations, error states, and trust. The Elo math was the easy part.