Research On University Teachers' Ability Model And Evaluation Based On Educational Big Data

In recent years,the rapid development of Internet technology has caused the importance of data in various industries.It has attracted widespread attention from researchers.Data has begun to penetrate into various industries and industries.Healthcare,finance,entertainment and education.The domestic application in the education field is mainly targeted at students,and there are few related studies focusing on teachers.Most of the related research based on data with teachers as the main body are qualitative analysis of teachers without quantitative judgments.In part of the quantitative analysis process,after selecting quantitative indicators and constructing a quantitative system,there is no analysis of the entire quantitative system.Verification of usefulness and reliability.Aiming at the above problems,this paper is based on big data of school education and uses neural network method to build a model of university teacher evaluation ability and explores the dimensions and weights of university teacher evaluation index system.The main research contents and results of the paper are as follows:Based on the research on the indicators of college teachers' ability in related literature,four primary indicators,11 secondary indicators,and three tertiary indicators were proposed.Based on these indicators,a college teacher ability evaluation system was constructed.The construction process of the evaluation model mainly includes:the proposal and determination of indicators,the determination and consistency of indicator weights,and the validity and usability of the evaluation model.A college of Central China Normal University was selected as the research object.First,according to the college teacher ability evaluation system constructed in the dissertation,the teachers of the college were calculated in various dimensions,and a questionnaire for teacher ability evaluation generated based on the evaluation system was issued to students.The results were counted.Then,the usefulness and reliability of the evaluation system were tested by using the curve fitting method and the Livingston distance method based on the teacher ranking obtained by the two methods.The experimental results show that the constructed teacher ability evaluation system has the following characteristics:Good usability;Finally,on the basis of proving the usability of the evaluation system,predicting the ability of teachers by creating models trained by neural networks.Experimental results show that the relative error of the model is small and the model's decision coefficient is as high as 0.9 or more,and the prediction effect is well trained.