Simulation of E-learning video recommendation based on virtual reality environment on English teaching platform

Abstract

E-learning video is an effective teaching tool, and virtual reality technology can enhance the learning experience. However, the current English teaching platform lacks the personalized and real-time feedback video recommendation system. Therefore, this study proposes an E-learning video recommendation system based on virtual reality environment, which aims to provide a personalized, interactive and real-time feedback learning experience. In this paper, the prototype of E-learning video recommendation system based on virtual reality environment is designed, and the simulation experiment is carried out on the English teaching platform. In the environment of the E-learning platform, human–computer interaction and entertainment media can enhance students’ learning process and assist in teaching work. This article analyzes the simulation of E-learning video recommendation based on virtual reality environment on English teaching platforms. The E-learning video recommendation system can create user profiles on the website based on their basic information and behavior, fully tap into their preferences, and provide personalized learning services for them. The recommendation system can be divided into two parts: offline and online. Offline systems are mainly responsible for creating video related content, while online systems store data in databases, allowing for real-time investigation and retrieval of data; Online systems can respond to user requests in real-time, and combining online extraction with user behavior analysis can generate the final recommendation results. While constructing an artificial intelligence platform for English teaching, it is also necessary to propose application strategies for English teaching and achieve modernization of curriculum teaching.