EdTech & E-Learning

Our models utilize Item Response Theory (IRT) and Knowledge Tracing. Instead of a static curriculum, the system evaluates the student's answer latency and historical accuracy. If a student breezes through a calculus module, the system instantly serves advanced material. If they struggle, it automatically drops down to prerequisite foundational exercises. In A/B testing across cohort sizes of 5,000+ students, this dynamic routing has increased course completion rates by 28%.

We architect WebRTC solutions using horizontally scalable Selective Forwarding Units (SFUs) like mediasoup or LiveKit, deployed on Kubernetes. When a massive university-wide lecture begins, the cluster auto-scales in seconds. Furthermore, by implementing 'simulcast', the server sends varying video qualities to different students based on their individual bandwidth, ensuring that a student on a poor connection doesn't drag down the video quality for the rest of the class.

Yes. All student Personally Identifiable Information (PII) is encrypted at rest using AES-256 and separated from performance telemetry data using anonymized UUIDs. We implement strict data retention policies that automatically purge student records upon graduation or account deletion. Our infrastructure undergoes regular third-party penetration testing to certify compliance with all federal and state educational privacy laws.