Adaptive Learning Recommendation Engine Database

Create a machine learning-enabled database schema in PostgreSQL that tracks individual student learning patterns and generates personalized curriculum recommendations. Design a normalized database structure that captures granular learning event data, including time spent, difficulty levels, and mastery progression. Implement a Python-based recommendation algorithm using pandas that can generate real-time learning paths with 85%+ accuracy, integrating machine learning model predictions directly into database queries.