| With the popularization of higher education in 21 st century,the national demands for educational background and higher quality education are increasing.The scale of higher vocational education in China has been rapidly expanded.Recently,the scale of higher vocational education has reached almost half of the higher education.As an integral part of higher education and an important part of higher education,higher vocational education is particularly important for students.The orientation of students in higher vocational education in China lies in the application of technical talents,that is,the training goal of higher vocational education is the cultivation of skilled and practical talents.With the rapid development of the information society,the types of work are becoming more diverse.In higher vocational colleges,the traditional talent training method guarantees the employment rate of graduates to a certain extent.However,shortcomings of the method and unreasonable cognition of students lead to the quality and stability of employment barely satisfactory.In the training stage of higher vocational and technical colleges,it is significant to predict the development tendency,and to guide the direction according to the specific situation of the students.Because of that,it not only helps students to clear the direction of learning and employment,but also lets them clearly understand their shortcomings.Meanwhile,it can also improve the learning efficiency of students,and make their learning methods more specific.In addition,the classification forecasting and career planning guidelines for students can train higher vocational education talents effectively,increase the utilization rate of higher vocational colleges,and improve the quality of employment.Therefore,the prediction of the development for higher vocational students has become an urgent problem to be solved.During the study period,this paper systematically investigates and summarizes the training programs and teaching modes of computer-related majors in higher vocational colleges in China.Through questionnaires,the data of 2017 and 2018 graduates were collected,and the collected data were pre-processed.The development direction ofstudents in higher vocational colleges and the factors affecting students’ development direction were qualitatively and quantitatively analyzed,and collected.The data of vocational college students’ development status is explained and analyzed.On this basis,the paper conducts in-depth research on data mining and clustering analysis,and compares and filters clustering algorithms according to different application fields and different clustering methods.This paper chooses K-Means algorithm as the core algorithm of student development prediction,and introduces corresponding feature attribute selection,equilibrium discriminant function and RBF neural network to improve and optimize K-Means algorithm.This paper analyzes the advantages and disadvantages of existing models and resources,and is oriented to the problems and needs of students in GUANGDONG ATV Professional Academy For Performing Arts.After a questionnaire survey of graduates in the past five years and feedback from students in the school,the clustering algorithm is used to Data analysis of basic personal information and employment status of graduates.Based on the analysis of a large number of data samples,the student development prediction model is constructed based on the optimized K-Means algorithm,which can be applied to the prediction of the development trend of higher vocational students,and the comparison test of prediction results is designed for the model.According to the test results,the accuracy of the higher vocational students’ development prediction model in the experimental detection stage is as high as 90%,which can meet the needs of the development forecast of higher vocational students,and plan the future development direction for the students of higher vocational colleges. |
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