AI Adaptive Learning System
Adaptive learning — not just "offer next lesson". This is dynamic model of student knowledge that tracks error patterns, learning speed, forgetting (Ebbinghaus curve) and rebuilds learning plan in real-time. Difference from linear courses: student goes only what needs, at pace suitable.
Knowledge Tracing Model
Deep Knowledge Tracing (DKT): LSTM/Transformer model predicting probability of correct answer on each skill from answer history. Korean 2023 research on 12,000 students: DKT adaptation reduces time to material mastery by 23% vs linear course at same final grade. Course completion rate increases from 15-20% to 45-60%.
| Approach | Personalization | Implementation Complexity | Data to Start |
|---|---|---|---|
| Rule-based | Low | Low | None |
| Item Response Theory (IRT) | Medium | Medium | 500+ students |
| Deep Knowledge Tracing (DKT) | High | High | 5000+ sessions |
| DKT + Spaced Repetition | Very High | High | 5000+ sessions |