The Vocational Education Evaluation Research Based On BP Neural Network

Since the implementation of the 11 th Five-Year plan,vocational education reform has always been a hot topic of education in China.In the central and regional governments of the eager care and active promotion,the teaching form of vocational education in China is constantly innovating,the teaching system is becoming more and more perfect,and the enrollment scale has been equal to the scale of the ordinary high school education.As an important part of the evaluation of students' curriculum development in vocational colleges,it has the functions of test results,diagnosis problems and information feedback functions,etc.It is of great significance and function to promote the overall development of students and improve the difficulties of teachers' teaching.How to build a set of scientific and reasonable evaluation index system to standardize,rationalize and unify the evaluation of vocational schools is a problem that needs to be considered in the reform of vocational education evaluation.To evaluate the performance of vocational education,we need to consider many factors that may affect the scores.Because of the different degree of influence on the evaluation factors or among the factors,the final evaluation results are difficult to express with appropriate analytical expressions.As one of the most widely used neural network models,the BP neural network has particularly strong nonlinear mapping ability,and it can approximate any continuous function with various precision.At the same time,the BP neural network has self-learning,self-adaptive and self-organizing ability.It has a good effect on solving the complicated problems of internal mechanism,and it can be used as a vocational school.The performance evaluation of lesson assessment provides new technical support.Through the investigation and analysis of Vocational Colleges and the reference of relevant literature,summarize the related factors which affecting the evaluation of vocational school curriculum,designs a reasonable evaluation index system and collect data according to the requirements.The MATLAB software is used to construct the BP neural network evaluation model which optimized by genetic algorithm,and the network is trained with enough scientific samples to make adaptive learning of the weight of the index,until the stopping condition of the learning is satisfied,and the global error of the network tends to be minimization.Then we input the data which collected from the index into the trained neural network model,and get the result of the student assessment.The conclusion shows that it is reasonable to use BP neural network to evaluate the vocational education curriculum.It can better overcome the influence of human factors on the evaluation results and ensure the objectivity and fairness of the students' evaluation.