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@article{192634,
        author = {Som Gharod and Suyash Devadkar and Ruhil Kamble and Sanket Umare},
        title = {Personalized Learning Analytics and Study Time Analyzer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {2136-2140},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192634},
        abstract = {This project focuses on developing a Personalized Learning Analytics and Study Time Analyzer system to help students improve their academic performance. The system analyzes students’ learning behavior, study patterns, and time usage to provide clear and personalized insights. It highlights strengths, weak areas, preferred study times, and subject-wise study trends through an interactive cloud-based dashboard. By offering meaningful feedback and study recommendations, the system helps students manage their time better and understand their learning habits. Overall, the project aims to make learning more effective, organized, and student-centric using intelligent data analysis.},
        keywords = {Personalized Learning, Learning Analytics, Study Time Analysis, Artificial Intelligence, Machine Learning, Educational Analytics, Student Performance Monitoring, Time Management, Cloud-Based Dashboard, Data Visualization.},
        month = {February},
        }