Digital Transformation Path of Foreign Language Education in the Process of International Communication Based on Multiple Regression Analysis

Abstract

In this study, feature mapping and dimensionality reduction analysis of raw educational data was performed based on the identification of eight influential factors, combined with sparse principal component analysis (sparse PCA) method. Afterwards, the kernel ridge regression method was used to calculate the multiple regression results of the processed principal component data to guide the transformation of digital teaching. The principal component regression equation for the effect of digital transformation of foreign language education is Y=4.093+0.394P1+0.231P2+0.202P3+0.103P4+0.070P5. P1-P5 represent resource application, equipment acquisition, equipment acceptance, students' learning attitude, and teachers' professional attitude, respectively, and targeted improvement of these aspects can effectively improve the effect of digitization of foreign language education and increase the success rate of its digital transformation.