10 math strands, 20 learning pathways, 1,180 adaptive missions. The AI tutor asks questions — it never gives answers. 103 misconception detectors. 8 languages. Dyscalculia accommodations. Any browser, any device.
Each strand is a structured learning progression — not a playlist. The adaptive engine selects the right mission at the right difficulty, and no skill is marked mastered until the student can transfer it.
The type of wrong answer is diagnostic. 103 misconception detectors across all 10 strands trigger specific repair prompts — not generic hints.
103 detectors total across all 10 strands. Shown above are examples — the full detection library is part of the adaptive engine.
The AI tutor monitors three signals to keep each student in the zone where struggle builds understanding rather than frustration.
Tracks scaffolding frequency. As independence grows, hints fade.
Measures whether skills learned in one mode apply in another — the evidence that understanding is durable.
Response time, retry rates, and pause durations estimate affect. The tutor intervenes before frustration takes hold.
The AI tutor never gives answers. It asks the question that leads the student to discover the answer themselves.
No skill is marked "mastered" until the student can transfer it to an unfamiliar context. The 5-mission sequence ensures understanding, not just pattern matching.
Every student generates an evidence packet per micro-skill. Teachers and districts see growth across nine measurable dimensions — not a single score.
Actively seeking pilot partners. QLM launched in April 2026. These evidence dimensions are designed and implemented in the platform but have not yet been validated with large-scale student data. We welcome research partnerships to validate measurement quality.
research@quantumlearningmachines.com
Designed to reach the students furthest from opportunity first.
The engine meets students where they are — age-appropriate engagement, ability-appropriate difficulty.
8 languages. Visual simulations mean language supports the experience but is never the gate.
Color-coded place values, graph paper overlay, enlarged numbers. The engine distinguishes symbol manipulation difficulty from quantitative reasoning difficulty.
Any device with a browser. No app to install. No IT ticket.
The teacher decides what to teach. The system provides data, simulations, and scaffolding.
Our measurement specifications are open and our benchmark results are published honestly, including results that do not favor us. We welcome research partnerships.
research@quantumlearningmachines.com
Interested in bringing adaptive math to your school or district? partnerships@quantumlearningmachines.com