A Dynamic Model for Blended Learning of University English Based On K-Means Clustering Algorithm

In the context of the new economic era, both the development and application of new technologies have put forward higher requirements for the cultivation of talents in colleges and universities. In order to address the shortcomings of the existing research on the dynamic model of blended learning of university English, this paper briefly introduces the learning support design and behavioral science theories as well as the K-means clustering algorithm. After the discussion of the selection of data collection and online learning behavior metrics for the university English blended learning platform, the blended learning model of the university English online platform and the evaluation model of the university English blended learning platform based on the K-means clustering algorithm are designed, and the clustering results of students’ learning behaviors calculated by the K-means clustering algorithm show that 128 learners have a completion degree of less than 0.8 in the five indicators. The K-mean clustering algorithm was verified to be effective in mining and analyzing learner’s behavioral characteristics.