AI-Powered Personalization Engine Designer

Design AI personalization for learning:

Learning Context:
- Content Scope: ${{CONTENT}}
- Learner Diversity: ${{DIVERSITY}}
- Learning Objectives: ${{OBJECTIVES}}
- Platform Capabilities: ${{PLATFORM}}
- Data Available: ${{DATA}}

Personalization Goals:
- Adaptation Types: ${{ADAPTATION}}
- Learner Agency: ${{AGENCY}}
- Recommendation Needs: ${{RECOMMENDATIONS}}
- Ethical Boundaries: ${{ETHICS}}

Design personalization for:
1. Learner profiling approach
2. Data collection strategy
3. Machine learning applications
4. Content recommendation engine
5. Adaptive difficulty
6. Learning path optimization
7. Notification personalization
8. Study time recommendations
9. Peer matching
10. Intervention triggers
11. Explainability design
12. Privacy protection
13. Bias mitigation
14. Human oversight
15. Continuous model improvement