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@article{174233,
        author = {Vedant Dalavi and S. R. Sontakke and Gaurav Jaiswal and Yash Ingole and Arihant Ganorkar},
        title = {Implementation and Results of an Intelligent Skill Development Platform for Youth},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {3300-3310},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174233},
        abstract = {The rapid growth of digital learning platforms has transformed education by providing learners with flexible, interactive, and personalized learning experiences. However, traditional Learning Management Systems (LMS) often lack intelligent features that can enhance student engagement and streamline the learning process. To address this gap, we developed the Intelligent Skill Development Platform for Youth, a MERN-stack-based LMS designed to offer programming and coding courses with an integrated intelligent search feature powered by Large Language Models (LLMs). This paper focuses on the implementation and results of the system, detailing the architecture, development process, performance evaluation, and user feedback.
The platform’s backend is built using Node.js and Express.js, ensuring efficient API communication, while the frontend is developed with React.js to provide an intuitive and user-friendly interface. MongoDB serves as the database for managing course content, user progress, and query responses. The key innovation of our system lies in the AI-powered search functionality, which enables learners to obtain instant, context-aware answers to their coding-related queries. This is achieved through seamless LLM integration, allowing real-time natural language processing for enhanced user interaction.
The paper evaluates the system’s performance using various quantitative metrics, including response time, scalability, and user engagement levels. Load testing demonstrates the platform's ability to handle multiple concurrent users with minimal latency, while qualitative feedback highlights improved learning efficiency. Comparative analysis with traditional LMS platforms shows a significant enhancement in user experience due to AI-driven assistance. Furthermore, we discuss challenges encountered during implementation, such as optimizing LLM responses, ensuring scalability, and maintaining data security.
The results indicate that integrating LLM-based intelligent search within an LMS significantly improves learners' ability to grasp complex programming concepts efficiently. The study concludes that AI-driven LMS platforms have the potential to revolutionize online education by making learning more adaptive and interactive. Future enhancements will focus on incorporating personalized learning recommendations and advanced analytics to further improve student engagement and performance.},
        keywords = {Intelligent Skill Development, Learning Management System (LMS), MERN Stack, Large Language Model (LLM), AI-powered Learning, Personalized Learning, Youth Empowerment, Educational Technology.},
        month = {March},
        }