A Study on Decision Tree Analysis Method of Teaching Quality Improvement for Teachers of Marketing in Higher Education Institutions

In order to explore the deficiencies in the teaching process of marketing majors in higher vocational colleges and further improve the teaching quality of marketing majors in higher vocational colleges.This paper utilizes the improved ID3 algorithm to construct the SLIQ data mining algorithm to improve the teaching quality of teachers of marketing majors in higher vocational colleges and universities.Using ID3 algorithm to build a decision tree to get the portraits of teachers and students, at the same time, in order to reduce the computational complexity of ID3 algorithm and the problem of multi-value bias, the concept of sample structure vector similarity is introduced, and the degree of information gain is optimized to get a more reasonable decision tree.On this basis, based on the improved ID3 data mining algorithm, a teaching quality assessment system for senior marketing majors based on SLIQ algorithm is designed, which identifies important factors affecting teachers' teaching quality by mining a large amount of data in the teaching process.The AUC value of the SLIQ data mining algorithm is 0.98, which can effectively improve the algorithm's generalization ability, and it has an excellent performance in the teaching quality assessment task.The performance is excellent.In this paper, we systematically identify "the principles of marketing" and "the degree of seriousness of teachers' homework correction" as the key factors to improve the teaching quality of marketing teachers.It provides a scientific basis for improving the quality of teachers' teaching.