The Application of Multiple Regression Model in Blended Teaching of Higher Mathematics

Abstract

Higher mathematics is a term used to describe complex mathematical ideas and subjects that go beyond the fundamentals of algebra, geometry, and number theory. Geometry, linear algebra, discrete mathematics, topology, and analysis are often covered. It entails creating fresh mathematical ideas and solving challenging issues by applying solid mathematical rationalization. Economics, statistics, mathematical modeling, and software for descriptive statistics are all areas covered by mathematics applications. Global concern is being raised by the falling number of students pursuing elevated amounts of mathematics. The underperformance and disinterest of students in mathematics may be attributed to a variety of issues. One cause of the drop is the knowledge gaps that arise when learners do not acquire or comprehend important mathematical ideas. It is essential to provide the best teaching strategy. Blended learning combines online and in-person instruction utilizing a range of tools and communication channels that are accessible to both students and instructors. In the setting of data processing and statistics, multiple regression analysis could serve as a helpful tool for teaching mathematics. Thus, we suggested using a multiple regression model (MRM) in blended higher mathematics instruction. Using performance measures and comparisons to existing methods, we assessed the efficacy of the suggested approach. The study results proved that MRM has provided an implementation cost of 45. According to the results, the proposed approach helps students learn mathematics in a more significant way.