A Study Based on Logistic Regression Algorithm to Teaching Indicators

Objective: This study aims to examine the factors that influence teachers’ choice regarding the importance of instructional indicators. Methods: Based on a logistic regression algorithm to survey university faculty on the importance of teaching indicators, and the resultant data were processed by binary logistic regression analysis. Results: 731 questionnaires were collected in total. We constructed 3 dimensions of basic construction development, practice cultivation construction, and innovation education development, concluding that the difference of age, education, education work time, and title category are the factors that influence the choice of teachers’ teaching goal emphasis level under each dimension, education constitutes an important influencing factor with the most profound level impact. Conclusion: Accelerate faculty gradient structure, strengthen teachers’ teaching awareness and enhance teachers’ sense of belonging in education career may become vital links to promote high quality construction and development of universities.