A Method for Constructing the Characteristics of English Majors in Vocational Colleges Based on Data Fusion of Educational Reform

This paper proposes a method for the construction of English major group characteristics in vocational colleges based on the integration of educational reform data. This method accurately extracts educational reform data from the official website of vocational colleges by using ETL tools in the database. Word segmentation and stop word processing are performed on these data to achieve data cleaning and integration. The processed teaching reform data of vocational colleges are integrated to form a comprehensive dataset. Based on this integrated dataset, the Analytic Hierarchy Process is used to accurately interpolate the missing values present. After completing the interpolation of missing values, advanced methods based on two-layer robust cross-mapping are further applied to deeply fuse the teaching reform data of vocational colleges, thereby generating high-quality fusion data of vocational college teaching reform. On this basis, a strategy for constructing the characteristics of English major groups is proposed, and the teaching effectiveness of the constructed English major groups is evaluated through a fuzzy comprehensive evaluation model based on the bat algorithm. The experimental results show that this method has strong effects on data integration, missing value interpolation, and fusion in vocational college education reform. At the same time, it can effectively build an English professional group for vocational college teachers, and the teaching effect of this English professional group is good.