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@article{180574,
        author = {Rachita Ajay Agrawal and Shrawani Kondawar and Durgesh Sawale and Achal Gupta and Prof. J.S. Pawar},
        title = {AI-Driven Student Career Counseling Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2211-2216},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180574},
        abstract = {This paper presents an AI-driven career counseling platform that provides personal educational streams and courses for students based on academic achievements and MCQ-based fitness assessment. The system provides separate interfaces for students and administrators. Students (after 10 and 12 class) receive branch -like science, trade or art -based on scores and test reactions. Further competence is provided for class 12 students, including power -specific alternatives such as B.E., MBBS, BBA, B.com, BJMC and more. The final recommendation is with a courtyard list of relevant colleges in India. Administrators can update the MCQ database and college entry. The aim of the platform is to change the general career councils with computer -driven guidance that corresponds to the student's ability and interests.},
        keywords = {Career Counseling, MCQ Analysis, Academic Stream Prediction, Student Profiling, Branch Recommendation, College Suggestion.},
        month = {June},
        }