University Teaching Evaluation Based on APriori Algorithm and Data Mining

In order to carry on the deep research to the teaching management data, analyze the deeper content, and make the teaching evaluation play a greater role, this is an urgent problem to be solved. So the data mining algorithm for information university teaching management system is put forward. Taking a technical college as an example, this essay uses data mining technology to cluster the classroom evaluation behavior. Based on the relationship between teaching evaluation data and students' achievement, this essay analyzes the specific factors that affect the teaching quality level. The key factors that determine teaching quality are deeply mined by association rules, and the specific influencing factors are found. Research findings that there is a direct relationship between teachers' teaching quality and evaluation level. For the teachers with excellent teaching quality, the corresponding grade evaluation is satisfactory and the confidence degree is 0.8. The confidence degree of basic satisfaction of teachers whose teaching quality is good is 0.67. The confidence level of excellent teaching method and satisfactory evaluation grade is 0.7, which is the same as the confidence level of basically satisfactory evaluation grade when the teaching method is good. Conclusion: The evaluation model is effective.