Analysis of Strategies for Enhancing Informatization Teaching Ability of College Teachers Combined with Mathematical Statistics Multiple Regression Models

Abstract

In this paper, from the perspective of education informatization, for the problem of teachers’ informatization teaching ability in colleges and universities, the loss function of the analysis of teachers’ informatization teaching ability in colleges and universities can be calculated by using a Logistic regression algorithm. In order to prevent the overfitting problem of multiple regression analysis, it is necessary to optimize the multiple regression analysis by regular transformation, and then construct the model of teachers’ informatization teaching ability based on multiple linear regression, and determine the research variables and regression equations in the model. Starting from the research objectives, the research objects and problems are determined, and two analysis methods, simulation analysis and statistical analysis, are used to empirically analyze the informatization teaching ability of college teachers. The results show that on the analysis of model instances, the correlation coefficients between the factors and the overall teacher educators’ informatization teaching ability range from 0.671 to 0.829, and there is a certain correlation between each factor and teacher educators’ informatization teaching ability. On the analysis of differences in teachers’ informatized teaching competence, the five competence constructs of Guangzhou college teachers’ education in technological literacy (P=0.653>0.05), instructional design (P=0.133>0.05), instructional implementation (P=0.584>0.05), evaluation development (P=0.287>0.05), and informatized teaching competence (P=0.413>0.05) do not significant differences exist. This study comprehensively analyzes the strategies for improving teachers’ informatization teaching ability in order to play some role in promoting the development of education informatization.

Keywords

• logistic regression algorithm
• loss function
• regular variation
• multiple linear regression
• informative teaching skills
• 97q80