Curriculum Adaptive Learning Path Generator

Create a Flask-based recommendation engine that dynamically generates personalized learning paths for students based on their prior performance, learning style assessments, and skill gaps. Implement a graph-based algorithm that can map prerequisite knowledge, suggest optimal learning sequences, and provide real-time difficulty adjustments. The system should support multiple learning domains (STEM, humanities) and include a robust logging mechanism to track recommendation effectiveness.