The Design of an Online Meditation Learning and Sharing Platform

As mindfulness meditation gains increasing recognition, many individuals still face challenges in accessing structured learning resources and community support. This study explores the development of a mindfulness meditation platform that integrates structured courses, an interactive forum, and an AI-driven personalized recommendation system to enhance user engagement and learning effectiveness. The platform adopts a B/S structure, uses the Vue framework to design pages, uses the Spring Boot framework to quickly build applications in the background, uses the MyBatis framework to efficiently handle database operations, and uses MySQL to manage the database. The platform leverages the DeepSeek API to provide tailored content suggestions based on user interactions, while the forum fosters peer support and knowledge exchange. To address potential scalability issues with AI-based recommendations, future improvements include developing an in-house recommendation model. Additionally, an anonymous posting option is proposed to encourage open discussions within the real-name forum. A user experience evaluation based on the HEART framework will assess key aspects such as satisfaction, engagement, and retention, guiding further optimizations. By integrating personalized learning and community-driven support, this platform aims to provide a comprehensive and scalable solution for mindfulness meditation practice.