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@article{187995,
        author = {Chinthakunta Sreeja and Apoorva and Abhinaya},
        title = {EDUMENTOR – Smart Student Performance & Learning Analytics Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {736-741},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187995},
        abstract = {Education today is rapidly transforming with the help of Artificial Intelligence (AI) and Data Analytics. Traditional academic management systems focus only on data storage and record maintenance but lack predictive and analytical insight. This paper presents EduMentor — a Smart Student Performance & Learning Analytics Platform that applies AI, Machine Learning, and automation to predict academic outcomes, monitor progress, and enhance institutional efficiency. The system uses FastAPI as the backend framework, scikit-learn for predictive modeling, and HTML/CSS/JavaScript for interactive dashboards. EduMentor integrates three modules—Student, Faculty, and Admin—linked through APIs for unified academic insights. The model predicts student performance with an accuracy of about 87%, supporting early interventions and data-driven decision-making.},
        keywords = {AI in Education, FastAPI, Machine Learning, Academic Analytics, Student Performance Prediction, EduMentor},
        month = {December},
        }