Optimization of Teaching Quality Improvement Path Based on Recursive Algorithm in the Construction of Higher Vocational English Gold Classes under the Background of Industry-Teaching Integration

The integration of industry and education refers to the in-depth integration of industry and education, which emphasizes the cultivation of students' practical ability and vocational quality.The integration of industry and education brings a new development direction for higher vocational education, and at the same time puts forward higher standards and requirements for higher vocational English teachers.In this paper, a new recursive Bayesian network structure algorithm is proposed based on RAI algorithm and CS algorithm, which mainly learns the Bayesian network structure by calling two functions recursively.Then based on the application effect evaluation model of recursive Bayesian network, the index system of classroom teaching evaluation is given based on the characteristics of classroom teaching, and the application effect is evaluated.The experimental results show that the optimization of the Bayesian network model can significantly improve the classification recognition reliability of the classifier, and taking the appearance score as a random effect, it can be found that the teacher's appearance difference has a significant effect on the teaching evaluation.The results of the study are of great significance to the construction of scientific English classroom construction as well as teaching quality evaluation system.