EduConnect Scalable E-Learning Platform Online is a M.Tech project topic for Computer Science & Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
EduConnect Scalable E-Learning Platform Online Project Details
| Abstract |
This paper presents the design of EduConnect, a secure, scalable, and smart web-based e-learning platform, specifically designed to improve the online education management process. Through this system, students are granted controlled and monitored access to learning materials, while teachers are given elaborate and powerful tools for the teaching process, including administrative functions, content upload, and management functions. EduConnect is built on a MERN stack. This means that the frontend is built using React.js which provides users with a light, dynamic, and interactive experience. Usersβ overall experiences are managed through backend services built on Node.js and Express.js as well as MongoDB to ensure data is stored in a manner that is
both efficient and consistent with a constantly changing data structure. Some fundamental functions that are incorporated include the management of each userβs lifecycle, including registration, secure logins, and profile management. Moreover, comprehensive management of each course is facilitated, including enrollment, participation, and creation of course content, uploading content, submitting assignments and participation in quizzes. This platform is also the only one with unsupervised and efficient management of monitoring studentsβ academic progress. Security is a top priority for the platform. As such, it employs a multi-layered security approach, including JWT-based user authentication, BCrypt password protection, secure transmission of data via HTTPS, secure RESTful APIs, and at the database level in order
to ensure safety.
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| Reference Paper |
EduConnect: A Scalable E-Learning Platform for Online Education Management |
| Domain |
Computer Science & Engineering |
| Sub-Domain |
Artificial Intelligence & Machine Learning / Computer Vision |
| PDF Download |
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| Get Help |
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