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@article{191539,
        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 = {12},
        number = {8},
        pages = {7330-7335},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191539},
        abstract = {Mentoring is a cornerstone of education, but traditional, resource-intensive models struggle with scalability, personalization, and high mentor workload. To address this, we propose the design and development of **Mentor Connect**, an intelligent student-teacher mentoring platform. Mentor Connect integrates Artificial Intelligence (AI) to facilitate **Teacher-AI Collaboration (TAC), reducing the burden on faculty mentors and providing structured, individualized student feedback. The platform is built on a unified Flutter framework for both frontend and backend, featuring advanced algorithms for optimal student-mentor matching, real-time progress tracking, goal setting, and robust data analytics. By modernizing administrative tasks and creating a data-driven mentoring ecosystem, Mentor Connect aims to enhance student engagement, improve professional growth, and contribute to higher teacher satisfaction and retention.},
        keywords = {Teacher-AI Collaboration (TAC), Mentoring Software, EdTech, Teacher Education, Student Support, Action Research, AI-assisted Feedback, Educational Technology, Flutter},
        month = {January},
        }