Construction and Practical Exploration of Intelligent Teaching Evaluation System in Higher Vocational Colleges and Universities

In this paper, we use the improved Apriori analysis method to construct an information management system for evaluating the teaching quality of teachers in higher vocational colleges and universities. Firstly, data such as students’ evaluations and teachers’ personal information are preprocessed, and then the improved Apriori algorithm is used to mine the data. Finally, for the multiple meaningful strong association rules mined out by the algorithm, the constitutive relationships between teachers’ age and title, age and education are found out to realize the improvement of teaching quality. The empirical analysis shows that the teachers with the title of associate professor are in the age of 50 years and above, and all of them have a bachelor’s degree. Most of the teachers in graduate school are above 35 years old. There is a strong correlation rule relationship between teachers’ education, teachers’ attitude and teachers’ age. Therefore, it is important to bring in more highly educated and highly titled teachers so as to improve the teaching level of higher vocational colleges and universities. The survey analysis shows that about 60% of the lecturers and evaluating teachers are supportive of this paper’s evaluation system to improve teaching quality.