Teaching ability evaluation of ideological and political teachers based on big data fuzzy clustering

Abstract

To improve the accuracy and utilization of the evaluation of ideological and political teachers’ teaching ability, this study proposes an evaluation method of ideological and political teachers’ teaching ability based on big data fuzzy clustering. According to the detected information resources and the characteristics that the smaller the average square residual value in the clustering is, the higher the similarity of information required by users is, the user needs to solve the minimum mean square residual value problem and information of given double cluster. The problem of information resource detection was transformed, and the missing features of the data were supplemented. The clustering minimum means square residual value problem with missing data was solved by using the idea of quadratic function, to realize the detection of information resources needed by ideological and political teachers in big data. Through the optimization process of the evaluation model of ideological and political teachers’ teaching ability, the method of big data fuzzy clustering and information fusion was used to cluster and fuse the information resources needed by teachers, to realize the evaluation of ideological and political teachers’ teaching ability. Results show that through the evaluation test of ideological and political teachers’ teaching ability, the evaluation accuracy and utilization rate of this method is higher than 95% in the evaluation cycle. The filling principle of multi-dimensional data missing features is better in the detection of information resources needed by users and promotes the improvement of Ideological and political teachers’ teaching ability.