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@article{199148,
        author = {Madhura Patil and Hiraman Jadhav and Prerana Mane and Shantanu kale},
        title = {SkillSwap – Peer to Peer Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {16078-16081},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199148},
        abstract = {The increasing demand for accessible and affordable learning platforms has led to the development of innovative knowledge-sharing systems. This paper presents SkillSwap, a web-based peer learning platform designed to facilitate reciprocal skill exchange between users. The system integrates artificial intelligence-based recommendation techniques, competency-based skill validation, and real-time collaborative tools to enhance the learning experience. Users register their expertise, upload resumes for automated skill extraction, and complete assessment tests to verify their competencies. Based on user profiles, skill requirements, and assessment scores, the proposed bidirectional matching algorithm identifies compatible learning partners and recommends optimal skill exchange opportunities. The platform also supports live interactive sessions through video conferencing, messaging, and collaborative whiteboards, enabling effective peer-to-peer learning. Security mechanisms such as encrypted authentication, secure data storage, and role-based access control ensure the protection of user information. The SkillSwap system demonstrates the potential of combining collaborative learning models with intelligent matching algorithms to build a scalable and community-driven learning environment.},
        keywords = {Skill Exchange, Peer-to-Peer Learning, Collaborative Learning, Recommendation Systems, Skill Matching Algorithm, Online Learning Platforms, Artificial Intelligence, Real-Time Communication, Knowledge Sharing.},
        month = {April},
        }