Distributed Federated Learning for Educational Research

Architect a privacy-preserving federated learning infrastructure that allows educational institutions to collaboratively improve machine learning models without sharing raw student data. Design a secure, decentralized computational framework that enables model training across multiple distributed datasets while maintaining strict data privacy and compliance standards. Implement advanced encryption and differential privacy techniques to protect sensitive information.