Intelligent Student Performance Prediction Framework

Create an automated machine learning pipeline that predicts student academic performance using multiple data sources, including historical grades, attendance records, extracurricular activities, and learning management system interactions. The framework should dynamically retrain models quarterly, generate personalized intervention recommendations, and provide explainable AI insights for educators. Implement robust data anonymization and ensure FERPA compliance throughout the predictive process.