Evaluation System Construction Industry for Kindergarten Teachers based on Digital Big Data Art

Abstract

In order to improve the development evaluation effect of kindergarten teachers, this paper analyzes the problems existing in the current development evaluation of kindergarten teachers. Moreover, for massive data, this paper combines big data technology to construct an evaluation system, and proposes a multi-parallel extreme learning machine model based on error compensation. In addition, this paper uses data mining algorithms to analyze the characteristics of the development evaluation of kindergarten teachers, analyze the system function structure according to the actual situation of the development evaluation of kindergarten teachers, and carry out the system role setting and the realization of system function modules. After constructing the complete system framework, the reliability of the system is analyzed through experiments, and the results of the experiments are displayed through statistical methods. From the research results, it can be seen that the intelligent system constructed in this paper can play a reliable effect in the development evaluation of kindergarten teachers.