This paper presents an extended study of the “Study Notion” e-learning platform, focusing on its technical framework, proposed real-world deployment, and theoretical benchmarking in the EdTech space. The paper explores the MERN stack-based architecture, potential integration of AI for adaptive learning, and highlights key areas like user privacy, responsive design, and inclusive accessibility. Additionally, a theoretical comparison with global platforms like Coursera and Udemy is provided. This enhanced model offers a roadmap for future development of inclusive, scalable, and intelligent learning systems.
Introduction
Study Notion is a learner-focused e-learning platform built using the MERN stack (MongoDB, Express.js, React.js, Node.js) for a modular and maintainable architecture. It emphasizes mobile-first responsive UI design with accessibility and clean navigation using Tailwind CSS. Security features include JWT-based authentication, with plans to add role-based access control and encrypted storage, aiming for GDPR compliance.
A proposed pilot study will evaluate platform performance by measuring course completion, user satisfaction, and usage analytics. The platform is theoretically compared with major players like Coursera and Khan Academy, highlighting its AI readiness, open-source flexibility, and modern tech stack.
Challenges such as digital literacy, device access, and learner isolation are addressed through tutorials, mobile optimization, and plans for live discussions. Future enhancements include VR/AR learning modules, blockchain certifications, sentiment analysis for burnout detection, multilingual support, and improved accessibility.
Deployment is managed via GitHub and cloud services, with plans to implement CI/CD pipelines for automated testing and deployment.
References
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