Application of edge computing and artificial intelligence in English MOOC assisted teaching instruction

The traditional MOOC teaching mode lacks personalized learning support and interaction mechanism. In order to solve these problems, this paper uses experimental methods to apply edge computing and artificial intelligence technology to English MOOC assisted teaching. This article collects learners' learning behavior data and personal information, and uses artificial intelligence algorithms to analyze and process these data. By analyzing learners' learning behavior and preference information, it can provide suitable learning materials and methods for each learner. In the system construction, edge computing technology is used to distribute computing tasks to edge devices, provide faster response speed and more stable services, reduce dependence on cloud servers, and avoid the impact of network latency and bandwidth restrictions on the learning experience. Edge computing can also provide better privacy protection. Learner's personal data does not need to be transferred to the cloud, but can be processed and stored locally. Through experimental verification, the application of edge computing and artificial intelligence in English MOOC assisted teaching mode can significantly improve the learning effect and satisfaction of learners, and enhance the learning experience.