Design, and Performance Evaluation of a Scalable E-Learning Platform with Adaptive Video Streaming and Automated Assessment using FastAPI
Design, and Performance Evaluation of a Scalable E-Learning Platform withAdaptive Video Streaming and Automated Assessment using FastAPI
Dr. Rais Abdul Hamin Khan1, Davidetta W. Saydee 2 and Abraham Ketter Jr.3
Depart of Computer Science and Engineering, Sandip University Nashik City
info@sandipuniversity.edu.in
Abstract:The rapid growth of online education has created a demand for scalable, efficient, and interactive e-learning platforms. However, many existing systems suffer from latency issues, inefficient video delivery, and lack of real time assessment capabilities. This paper presents “Learn Fast,” a high-performance e-learning platform built usingFastAPI, integrating adaptive video streaming (HLS) and automated quiz evaluation. The system leverages asynchronous processing, Radis caching, and optimized database interactions to improve scalability and response time. Experimental evaluation using load testing demonstrates significant improvements in latency,throughput, and concurrent user handling. The proposed system provides a robust, scalable, and efficient architecture suitable for modern digital education environments. Keywords: E-learning, FastAPI, Adaptive Streaming, HLS, Quiz Automation, Scalability, REST API, Redis