Automated Student Performance Predictive Analytics Pipeline

Design a Laravel-based data pipeline that integrates student assessment data from multiple sources (LMS, exam systems, classroom management tools) and creates a predictive machine learning model to forecast student performance risks. Implement automated data cleaning, feature engineering, and periodic model retraining using PHP's machine learning libraries like PHP-ML. The system should generate automated intervention alerts for at-risk students, including personalized recommendation workflows.