EdTech / AI
Educational / Cognitive Technology Platform
An adaptive learning and cognitive-assessment platform that adjusts to a learner's demonstrated understanding.
Overview
A cognitive-technology project exploring how AI can personalize learning paths and assess understanding beyond simple right/wrong scoring.
Problem
Traditional e-learning content is static — every learner sees the same material regardless of what they already understand, which slows down capable learners and leaves gaps for others.
Approach
We designed a system that models learner understanding over time and adapts content sequencing and assessment difficulty accordingly, combining a rules-based curriculum graph with a lightweight ML model for mastery estimation.
Architecture
- 1Curriculum graph & content model
- 2Mastery-estimation model per learner, per concept
- 3Adaptive sequencing engine
- 4Learner-facing web application and educator analytics dashboard
Technology
Results
- Learning-gain improvement
- Indicative — see note
- Concepts modeled
- Indicative — see note
- Active pilot learners
- Indicative — see note
This case study uses indicative placeholders pending publication of our verified pilot results.
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