A study on the application of creative writing in literature teaching based on multiple linear regression algorithm

Abstract

Abstract Under the background of the big data era, the rapid development of the Internet has driven the development of the education field. The traditional creative writing teaching is hardly suitable for the new curriculum reform requirements, prompting the rapid rise of creative writing and being highly recognized by the National Education Bureau. This paper applies creative writing based on multiple linear regression algorithms, i.e., teaching literature and education. Firstly, we understand the formula and principle of multiple linear regression algorithm, establish multiple linear models, extract and matrix students’ characteristic data, collect students’ data when learning on the online platform, pre-process the collected data, and analyze the performance and behavior of creative writing based on the end element linear regression algorithm. The results show that the number of clustering centers and visits are linearly correlated with the student’s grades, final overall grades, and test scores and that the student’s grades eventually improved to above 90. This study identifies the extent to which learning behaviors impact students’ final grades, allowing teachers to refine their teaching methods by selecting the learning styles that have a greater impact on students’ final grades among the many online platform student activities. It is conducive to improving cultural literacy and creative writing skills and has historical significance for developing Chinese literature and education.