Practical Reflections on Enhancing Cultural Confidence in English Education in Colleges and Universities under the Big Data Platform

Abstract

Day by day, we are realizing the goal of the great rejuvenation of the Chinese nation, which necessitates the development of sufficient cultural self-confidence. The amalgamation of traditional culture and English learning is an essential prerequisite for us to effectively communicate the Chinese story to the world. This paper proposes an optimized ridge regression model with regularization constraints to enhance the preprocessing of cultural data. Subsequently, we propose a statistical model for analyzing the teaching styles of English texts from four perspectives, taking into account the characteristics of English language teaching and the cardinal text statistics algorithm based on word frequency optimization. This model’s analysis revealed that textbook articles reflecting traditional Chinese culture accounted for only 1.8% of all types, resulting in an uneven distribution of grades. Following the implementation of improvements to tackle this issue, 74.86% of the students expressed their belief that enhanced teaching could bolster their cultural confidence. Similarly, 86.6% of the teachers expressed their belief that incorporating Chinese culture into English teaching could enhance students’ cultural awareness, and 90% of the teachers believed it could boost students’ identification with Chinese culture and cultural confidence. It shows that the new teaching method optimized by conducting textual statistical analysis helps to bring into play the role of English education in colleges and universities in enhancing cultural self-confidence.

Keywords

• ridge regression
• chi-square text statistical algorithm
• text style analysis
• cultural self-confidence
• english language teaching
• 62-07