Edushare - AI Driven Online Learning & Performance Analytics Platform

This paper has presented EduShare, a comprehensive, full-stack AI-driven online learning and performance analytics platform developed using the MERN technology stack. EduShare addresses substantive deficiencies in existing LMS platforms through an integrated feature set encompassing real-time learner analytics, role-based access control, dual payment gateway integration, automated certificate generation with integrity verification, and responsive user interfaces. The experimental evaluation established that EduShare achieves competitive performance characteristics: an average API response time of 142ms at 50 concurrent users, scalable throughput of 195 req/sec at 500 concurrent users, and a sub-0.1% error rate under standard load conditions. The multi-layer security architecture withstood automated penetration testing without yielding critical vulnerabilities. Comparative analysis against Moodle, Canvas, Coursera, and Blackboard affirmed EduShare's superiority in AI analytics integration, page load performance, and feature comprehensiveness within an open-source framework. The research confirms that the MERN stack constitutes a viable and performant foundation for production-grade educational platforms, and that integrated AI analytics are achievable within a full-featured LMS without architectural complexity unacceptable for resource-constrained institutions. EduShare's cloud-ready, containerizable architecture provides a clear scalability pathway from single-institution deployment to multi-tenancy cloud service. Future research directions include replacement of the rule-based analytics engine with deep learning models, blockchain-based certificate verification, microservices decomposition, and live streaming integration. The platform's open-source availability is intended to facilitate community contribution and academic replication, advancing the collective understanding of AI-enhanced educational technology platforms.

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