Research On Configurable Teaching Quality Evaluation System And Evaluation Methods

Teaching quality is an important indicator of high-precision college education quality,and it will indirectly affect the quality of students' training.In order to achieve long-term development,colleges and universities must pay attention to the quality of teaching.At present,the content,form,and system of teaching evaluation are different in each university,and each has its own characteristics.In the process of productization,it is very important to build an evaluation model that can adapt to different colleges and universities,different evaluation roles,and take multi-factor and multi-level index content into consideration.At the same time,with the deepening of informatization,the databases of various universities have accumulated a large amount of teaching evaluation data.How to use these data to improve the quality of teaching has become the focus of teaching managers.This paper builds a universal evaluation system model based on BOM,and deeply digs score data and subjective text from both quantitative and qualitative perspectives.It can not only help teaching administrators discover the advantages and disadvantages of teachers in teaching,but also discover the factors that affect teaching,and provide decision support for higher schools to improve teaching quality.The main work of this article is as follows:(1)The product configuration method based on BOM realizes the adaptive dynamic configuration design of the university teaching quality evaluation system.Users can configure a teaching quality evaluation system suitable for the school according to the individual needs of the school.Through this design,allowing users to participate in configuration autonomously reduces their dependence on software vendors.At the same time,it reduces the possibility of subsequent users needing to revise the system due to changes in the teaching evaluation system and content,and improves the maintainability of the system.(2)Analyze the score data in the teaching quality evaluation system from a quantitative perspective,and build a decision tree based on the fusion radar chart-C4.5 algorithm to predict the teacher's grade.When using radar charts to analyze data,the polar coordinate method is used to solve the problem that traditional radar charts cannot reflect the importance of indicators.And compared with the fusion method and the traditional classification algorithm,the experimental results show that the fusion method prediction results are more accurate.(3)Analyze the subjective evaluation data in teaching quality evaluation from a qualitative perspective,and propose an improved PSO-SVM algorithm for sentiment analysis,And through the LDA theme model to extract subject words,mining teachers' flash points and deficiencies.The algorithm has been improved from the initial particle swarm,and weight.Compared with the standard particle swarm optimization algorithm,it is found that the improved method improves the classification performance.(4)Develop teaching quality evaluation system,which mainly includes four modules of teaching quality evaluation system configuration module,teaching quality evaluation file setting,teaching quality evaluation statistics and teaching quality analysis results,and displays related interfaces.