AI-Powered Adaptive Learning Platform for K-12
A K-12 edtech company had a static content library with no personalisation, resulting in 62% student drop-off within 30 days.
Team
7 engineers + 2 learning scientists
Timeline
16 weeks end-to-end
Client
K-12 EdTech Company
Outcomes Delivered
71%
Student Retention Improvement
34%
Learning Outcome Score Increase
2.8×
Daily Active Usage Increase
How we delivered it
Analysed 2 years of student interaction data to identify the 12 strongest predictors of learning outcome and dropout risk.
Built a knowledge graph of 8,000 learning objectives with prerequisite relationships, enabling the engine to identify and fill knowledge gaps.
Developed a content difficulty adjustment algorithm that modifies question complexity in real-time based on the student's recent performance trajectory.
Implemented a parent dashboard showing weekly learning progress, time-on-task, and personalised recommendations for at-home practice.
Ran an 8-week A/B test comparing adaptive vs. linear learning paths — 34% better learning outcomes confirmed before full rollout.
What we built
Built an adaptive learning engine that adjusts content difficulty, pacing, and format based on individual student performance data.
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