Adaptive Learning Path Generator with Machine Learning

Design a Python-based adaptive learning recommendation system that uses machine learning algorithms to dynamically adjust educational content difficulty based on individual student performance. Implement a predictive model using pandas and scikit-learn that tracks student progress across multiple subjects, identifies knowledge gaps, and generates personalized learning paths. Include functionality to weight previous performance, learning style assessments, and real-time skill progression tracking. The system should output a JSON-based curriculum recommendation with confidence scores and suggested learning interventions.