Research on Level Assessment of English Teaching Model Based on K-Means and Information Fusion

According to the large amount of data existing in the level assessment of the English teaching model, the models cannot be classified correctly. Thus, a model combining the K-means algorithm and data fusion is proposed to estimate the level of English lectures. First, the indicators under the constraints are modeled; Second, the regression model is applied for the information modeling, and the information parameter is used for the limited information; finally, information is fused that the technology is related to the algorithm technology to cluster and integrate various indicators of the level of English lectures. Based on the parameter, a lecture resource allocation plan suitable for English teaching is suggested. The test result shows that the model clusters the information fusion, makes teachers’ teaching ability assessment more accurate, and effectively utilizes teaching resources.