The College English Teacher Behavior and Teaching Effect Based on Big Data Technology

Abstract

In order to explore the correlation between college English teacher behavior and teaching effects, this paper applies data mining technology to related research. Moreover, this paper uses Bloom Filter to represent the efficiency of insert queries and space usage of dynamic data sets and designs a multichannel balanced matrix Bloom Filter. In addition, this paper uses the longest prefix matching filling algorithm when selecting the element insertion position in multiple candidate Bloom Filters, and uses this algorithm to process the college teacher behavior and teaching effect data. Finally, this paper combines investigation and experiment to conduct research. Through the investigation, it can be seen that the teaching behavior of college English teachers will have a certain impact on students, and the positive behavior of teachers can effectively improve the teaching effect, which can be used as a reference for the formulation of subsequent teaching plans.