Construction of Teaching Performance Evaluation System for College Teachers Based on Data Mining

Abstract

Data mining has become an important means to improve the level of educational management under the background of big data. In this paper, the CART decision tree algorithm of data mining is applied to the performance management of college teachers. On the basis of statistical data, the factors affecting teaching quality such as teaching attitude, teaching methods and teaching preparation are taken as decision attributes to construct a decision tree. The specific construction process of CART decision tree algorithm in teaching performance evaluation of university teachers is illustrated by examples, and the classification model of teaching performance based on CART tree is generated. It is found that teachers who are fully prepared for teaching often show good teaching attitudes and better teaching performance. For the staff with good teaching quality but low teaching preparation score, if they have good teaching means or good teaching attitude, their teaching performance will be higher; If the teaching method is not skilled or the attitude is not good, the performance is average. It can be seen that teaching performance and teaching quality, teaching preparation, teaching means and teaching attitude are mutually restricting and influencing each other. Finally, targeted and reasonable performance evaluation suggestions are put forward.