Application of English education big data system based on multi-source information fusion and machine learning

For administrators in the field of education, the data generated in the actual education process is difficult to achieve effective management due to its large amount of information, complex structure and multiple types. However, in the actual construction of education informatization, it is impossible to explore the laws and development trends of education information only by manual analysis, so it is difficult to obtain effective concepts and relevant views. College education administrators cannot fully optimize the process of teaching diagnosis and reform through education informatization. Based on this background, this research introduces machine learning technology to achieve technical support for the integrated application of educational data. This paper focuses on the design and construction of an English teaching management data analysis system for college teaching, which combines machine learning technology with multi-source information technology. The system is mainly composed of hardware layer, data layer, service layer and application layer, which can assist teaching and realize learning career planning, faculty authority management, curriculum data modification, teaching resource allocation and scientific research review. The simulation results show that this big data system has high processing efficiency, and is superior to other algorithms in terms of mean value and FVDF extreme value, so it can effectively assist English teaching management. This paper completes the design of English education big data system by introducing machine learning and multi-source information fusion into the field of education.