Adaptive Learning Path Recommendation Engine Architecture

Design a machine learning-powered recommendation system that dynamically generates personalized learning paths for students based on their performance, learning style, and knowledge gaps. Create a modular architecture that can integrate with existing Learning Management Systems (LMS), using microservices and event-driven design. Include mechanisms for real-time skill assessment, adaptive content selection, and predictive learning trajectory modeling. Provide a comprehensive system design document with sequence diagrams, technology stack recommendations, and scalability considerations.