In today's fast-paced world, learning English has become a necessity for many people. With the emergence of technology, mobile learning platforms have become an effective way to learn English while traveling. The research and design of mobile English learning platform based on collaborative filtering algorithm is a promising way to improve the efficiency of language learning. Collaborative filtering algorithm is a technology used in recommendation systems. It predicts user preferences by analyzing users’ past behaviors and interests. By implementing this algorithm on a mobile English learning platform, users can obtain personalized recommendations for learning materials and exercises based on their personal needs and proficiency. The research and design of such a platform involves extensive data collection and analysis to create accurate user profiles. This includes tracking user activity, analyzing feedback, and monitoring progress. In addition, the design of the platform must have intuitive navigation, engaging content, and interactive features to maintain user motivation. In general, the development of mobile English learning platform based on collaborative filtering algorithm has great potential, which can provide personalized and effective learning experience for users around the world, thus completely changing language education. This article constructs a network model architecture for a mobile learning system based on mobile short message service and mobile internet technology. Analyzed the characteristics of learning in mobile environments, discussed the system software and hardware composition and key technologies; At the same time, by analyzing the roles of two major elements in teaching: teachers and learners in the system, the learning methods in mobile environments were studied, the system modules were planned, and the entire teaching process was discussed. A learning resource organization model and a dissemination model were proposed.