A Study on the Relationship between Multiple Regression Analysis and Students’ Achievement Improvement in Higher Education English Teaching

Students’ English learning achievement is affected by many factors, and the study found that there is a significant correlation between the English teaching process on the improvement of students’ English achievement, especially the teaching design. Based on this, this paper analyzes the correlation between English teaching design and students’ academic performance improvement in colleges and universities using the multiple linear regression method. Based on the multiple covariance problem in the multiple linear regression model gives the two-parameter algorithm optimization at the α level, and finally applies the optimized multiple linear regression model by example, and gets the conclusion that the optimized multiple linear regression model with the two-parameter algorithm optimization at the α level is feasible. The main research results are as follows: after this paper improves the parameter algorithm of the model on the α level, it is found that the fit of the model also reaches 85% under the influence of multifactor (more than 5), which proves that this paper is feasible for the improvement of the two parameters on the α level. The t-values of the independent test results for the five dimensions of teaching objectives and content are 6.765, 4.792, 3.163, 5.226, and 4.123, respectively, and their significance is less than 0.01, which proves that there is a significant correlation between the five dimensions selected in this paper about the design of English language teaching and the improvement of the English language learning achievement. The predictor variables chosen for the regression process are able to explain the response variables to a large extent, so the model can be used to predict improvement in English achievement. © 2024 Yi Li, published by Sciendo.