Real-Time Student Engagement Predictive Monitoring

Create a complex machine learning system that uses time-series analysis and multivariate predictive modeling to forecast student engagement levels in online learning environments. Utilize advanced feature engineering techniques to incorporate behavioral metrics, interaction logs, assessment performance, and temporal patterns. Implement a real-time alerting mechanism that can proactively identify students at risk of disengagement and suggest targeted interventions.