Eucliv
A machine learning-powered tool that adapts to how students learn, surfacing what needs more attention and when.
What is Eucliv?
Eucliv is a learning support tool that uses machine learning to help students understand what they know, what they don't, and what to focus on next.
It doesn't replace the teacher. It gives teachers — and students — a clearer picture of where learning is actually happening and where it isn't.
The problem it solves
Students often don't know what they don't know. They study what feels familiar, skip what feels hard, and arrive at assessments with gaps they didn't see coming.
Teachers face the opposite problem: they have a sense of where students are struggling, but not always the data to act on it quickly or confidently.
Eucliv closes this gap — not by collecting more data, but by making the data that already exists more useful.
How the machine learning works
Eucliv learns from patterns in how students interact with material: how long they spend on certain concepts, which questions they get right on the first try versus after multiple attempts, and how performance changes over time.
From these patterns, it surfaces:
- What needs review — concepts where a student's confidence is declining
- What's ready to advance — areas where mastery is evident
- What to prioritize — a focused view of where effort will have the most impact
The goal is not to track students but to support them. Every signal Eucliv uses is in service of a single question: what does this student need right now?
What makes it different
Most adaptive learning tools feel like testing engines. Eucliv is designed to feel like a study partner — one that is paying close attention and knows when to push and when to slow down.
Who it's for
Eucliv is designed for secondary and post-secondary students who want to study more effectively, and for teachers who want a clearer window into where their students actually are.
Status
Eucliv is in early research and design. We are working through the core ML architecture and beginning conversations with educators about what meaningful adaptive support actually looks like in practice.