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@article{179188,
        author = {Mohammed Poonawala and Abhilash Dash and Gargi Nakil and Jeet Bhalerao and Dr. Suvarna Pawar},
        title = {AI-Based Personalized Learning System for Skill Development},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5718-5722},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179188},
        abstract = {The diversity in individual learning preferences has long posed a challenge in the field of education. Conventional study techniques often fail to accommodate the varying modalities through which students absorb information most effectively. This paper presents the design and methodology of an AI-based learning system that identifies a user's ideal learning modality using the VARK framework—Visual, Auditory, Reading/Writing, and Kinaesthetic. By tracking user performance and adapting learning delivery through machine learning models like K-Means clustering and Support Vector Machines, the system dynamically refines its recommendations. Additionally, it incorporates proven study techniques and gamification to enhance user engagement and retention.},
        keywords = {K-means clustering, Learning modalities, SVM, VARK Theory.},
        month = {May},
        }