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@article{175664,
        author = {S.Deepa and K.Tharani and R.Yuvaraj and M.Dhanush and M.S.Sudharshan},
        title = {EMPOWERING FUTURE LEADERS: TAILORED CAREER GUIDANCE FOR YOUNG ASPIRANTS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3949-3954},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175664},
        abstract = {Career Decision is an important stage in a student's educational journey, especially after 12th grade when selecting the future career path. Methods of traditional counseling, although valuable, often rely on academic scores and lack individual, overall assessment. Many students, especially in rural areas, face limited access to expert guidance, leading to poorly informed career options. To remove these challenges, this research proposes an automated student career guidance system (SCGS). The SCGS collects detailed students including psychological and cognitive assessment as well as academic scores, interests and additional activities. It processes this data using a decision -making algorithm, which is extended by a trained machine learning model on the success pattern of career to recommend the appropriate career path based on individual profiles. SCGS has a user-friendly dashboard displaying individual career options, skill requirements, educational paths and online teaching resources. Its scalability ensures that it acts efficiently to many students, making it ideal for undescribed areas. Made with python (flask), MySQL and bootstrap, it is cost effective and easy to deploy. SCGS is dynamic, which is updating themselves to enhance themselves, which aligns with job market trends. By integrating intelligent data analysis, SCGS emphasizes students to create informed career options, to bred down intervals in traditional counseling, and promote satisfaction of long -term career.},
        keywords = {Student Career Guidance System (SCGS), career decision-making, psychological assessment, cognitive assessment, academic performance, machine learning model, decision-making algorithms.},
        month = {April},
        }