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@article{205159,
        author = {Navathar Rohit Mahesh and Kakade Sujit Ashok and Akhare Jayesh Mohan and Prof. Shyamsundar Magar},
        title = {Design and Implementation of Mentor Connect: An AI-Driven Student–Teacher Mentoring Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {5730-5736},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205159},
        abstract = {Mentoring is essential for academic achievement and professional growth; however, conventional mentoring systems are often limited by scalability issues, inefficient data management, and insufficient personalization. This paper presents the design and development of Mentor Connect, an AI-enabled student–teacher mentoring platform that integrates mentoring activities with institutional management functions. The system follows the Agile Software Development Life Cycle (SDLC), supporting iterative development and adaptability to changing requirements. A layered client–server architecture is implemented using Flutter and Firebase to ensure scalability and maintainability. Object-oriented design principles are applied to achieve structured data modeling and modular implementation. Core functionalities include role-based authentication, attendance tracking, leave and gate pass management, complaint handling, and analytics-driven reporting. In addition, AI-assisted mentoring features provide personalized feedback and support informed decision-making.},
        keywords = {Mentor Connect, AI-Based Mentoring, Agile SDLC, Academic Management System, Object-Oriented Design, Role-Based Access, Flutter},
        month = {June},
        }