Authors - Anuj Kothawade, Ishan Patra, Pravin Chavare, N. S. Shirude Abstract - The rapid digital transformation of higher education emphasizes the need for robust, data-driven platforms to monitor and enhance student learning. However, many institutions rely on closed, third-party learning management systems that restrict direct access to raw educational data and limit customized analytical capabilities. To address this gap, this paper proposes a scalable educational assessment and learning analytics platform that grants educators complete data sovereignty. Built on a modern stack of TypeScript, React and Tailwind CSS over an owned, directly accessible Firebase backend, the system enables secure, unhindered access for granular data mining. The platform monitors a range of college assessment activities, targeting quizzes and practical coding tests, and uses role-based authentication and custom data-fetching hooks to process student interactions into comprehensive performance metrics. A distinguishing feature is its integrated client-side PDF generation, which instantly produces detailed analytical score reports that serve a dual pedagogical purpose: empowering teachers with actionable insights to adapt instruction, while giving students personalized, self-reflective feedback for continuous improvement. Validated on a controlled pilot, the system achieved 95% overall accuracy, an 85% quiz-evaluation accuracy, a 28% improvement in student engagement, a 40% reduction in report-generation time, and a 92% system-usability score.
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