Automated Student Performance Trajectory Prediction Pipeline

Design a comprehensive Python data pipeline using scikit-learn and pandas that ingests student performance data from multiple learning management systems, performs multi-dimensional predictive analysis, and generates automated early intervention recommendations. The system should integrate historical academic records, engagement metrics, and learning style indicators to create personalized risk assessment models. Include robust error handling, data anonymization protocols, and a Flask-based dashboard for administrative visualization.