Adaptive Learning Path Recommendation Engine

Design a machine learning-powered recommendation system that creates personalized learning paths for students based on their academic history, learning style, and performance metrics. Develop a complex algorithm that can dynamically adjust course recommendations in real-time, considering factors like prior knowledge, learning pace, and skill gaps. Implement a robust feature engineering approach that incorporates both structured and unstructured data sources, including student feedback and interaction logs. Create a scalable solution that can be integrated with existing learning management systems.