Evaluation on the Application of Data Mining in the Evaluation System of Teaching Ability of Double Teacher Teachers

This article mainly focuses on the evaluation data of students in a certain major in a university, exploring the underlying information and patterns through various analytical methods, in order to provide scientific basis for teachers' teaching improvement and management decision-making. This article also uses correlation analysis method to explore the correlation between different indicators and their impact on student evaluation, and uses factor analysis to reinterpret the original evaluation index system, identifying several main factors that reflect students' perspectives, such as teacher teaching skills, knowledge level, attitude, and emotions, and uses data mining technology to discover the causal relationship between evaluation indicators. In the evaluation of student satisfaction for dual teacher teachers, the proportion of highly satisfied students is 33%, and the proportion of satisfied students is 25%. Through the above research, important references and support can be provided for teachers, professional leaders, and educational reform leaders, helping them better formulate relevant policies and measures, and promoting the continuous improvement and innovation of education and teaching quality.