Skill Swap: An AI-Integrated, Multi-Lingual Peer-to-Peer Learning Platform

In recent years, digital learning platforms have significantly expanded access to educational resources worldwide. However, many platforms rely on paid or subscription-based models that limit accessibility for financially constrained individuals. This paper introduces Skill Swap, a decentralized peer-to-peer learning platform designed to facilitate knowledge exchange without monetary transactions. Users offer specific skills while requesting others in return, enabling collaborative learning through mutual exchange. The system integrates intelligent matching algorithms, multilingual user interface capabilities, and secure communication mechanisms. Matchmaking employs string-similarity analysis via PHP-based Natural Language Processing (NLP) functions to identify compatible learning partners. Security measures include bcrypt password hashing, secure session management, and prepared database statements to prevent SQL injection. The platform is built with HTML5, CSS3, JavaScript (ES6), PHP, and MySQL and supports English, Hindi, and Gujarati localization. A user evaluation involving 25 participants showed a match relevance rate of 68% across 120 generated matches, demonstrating the practical feasibility of an inclusive, cost-effective, peer-driven knowledge exchange ecosystem.