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@article{199282,
        author = {Kushagra Upadhyay and Lakshay Shrivastav and Shashikant Mourya},
        title = {Design and Implementation of an AI-Powered Interactive Study Assistant with Adaptive Learning Analytics and Intelligent Content Generation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13014-13021},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199282},
        abstract = {The proliferation of digital learning resources has exposed a critical gap: students lack intelligent, unified tools that simultaneously generate study content, track academic progress, and provide adaptive guidance. This paper presents the design and implementation of an AI-Powered Interactive Study Assistant—a full-stack web application built with React.js (Vite), Node.js, and Express.js, deployed on Vercel and Render. The system integrates a prompt-based AI engine to deliver eleven core features including document intelligence, quiz generation, summarization, flashcards, an AI tutor, smart recommendations, learning insights, a progress dashboard, knowledge graph visualization, goal tracking, and a motivational UI. Empirical evaluation involving 80 undergraduate students demonstrates significant improvements in study consistency (65%), concept retention (61%), and user satisfaction (SUS score: 88.3). The platform establishes a reproducible blueprint for building scalable, AI-driven academic tools.},
        keywords = {Artificial Intelligence, Study Assistant, React.js, Node.js, Adaptive Learning, Quiz Generation, Concept Map, Progress Tracking, Prompt Engineering, Full-Stack Web Application.},
        month = {April},
        }