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EduSmart – A Web Based Student Platform for Interactive Learning and Development
Published Online: July-August 2026
Pages: 83-87
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20260604009Abstract
The rapid growth of online education has increased the demand for intelligent learning platforms that provide personalized, interactive, and engaging educational experiences. This paper presents EduSmart, a web-based intelligent learning platform designed to enhance student engagement through gamification, artificial intelligence, and real-time learning analytics. The proposed system is developed using the MERN stack (MongoDB, Express.js, React.js, and Node.js) and follows a client-server architecture to ensure scalability, security, and efficient data management. EduSmart incorporates multiple educational features, including secure user authentication using JSON Web Tokens (JWT) and bcrypt, personalized learning dashboards, interactive multimedia lessons, quiz-based assessments, achievement tracking, and progress analytics. A key contribution of the platform is the integration of an AI-powered assistant based on the Google Gemini API, which provides instant academic support by answering students' queries in real time. The system also includes dedicated faculty modules for course management, student performance monitoring, and analytics, enabling efficient administration and personalized guidance. Cloudinary integration is utilized for secure media storage, while responsive user interfaces developed with Tailwind CSS ensure accessibility across multiple devices. The implemented platform demonstrates improved learner engagement through gamification techniques such as experience points (XP), achievement badges, and learning streaks, while offering comprehensive performance monitoring for both students and instructors. Experimental evaluation indicates that the proposed architecture provides a secure, scalable, and user-friendly environment for digital learning. EduSmart effectively combines modern web technologies, artificial intelligence, and learning analytics to create an adaptive educational ecosystem capable of supporting future intelligent e-learning applications.
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