Construction and Application of Farmers’ Practical Teaching System in Vocational Education Based on Big Data Mining Technology

Abstract

With the establishment and perfection of social market economy, China has made changes to the disadvantages of farmers’ vocational education system, such as singleness, backward educational means, and backward levels. Compared to traditional forms of farming, problems related to lack of farming expertise, poor scientific and technological awareness, and weak labor skills are analyzed by applying big data mining technology to retrieve key issues in order to establish a professional education system. Data mining can meet the needs of farming knowledge and rapidly develop into an automatic information farming model, which is an effective way to maximize and enhance professional knowledge. The establishment of a professional education system will train most scientific research members and further enhance diversified labor productivity. The experimental summary of this paper is as follows: (1) the relevant data need to be predicted before and after, the predicted experimental data will effectively improve students’ grades, which is beneficial to the development of practical teaching, and the pretreatment stage plays a substantial role. (2) Among the three algorithms, the adaptive function of genetic clustering algorithm is obviously better than the other two algorithms, and the adaptive curve is relatively stable. (3) The comprehensive assessment of the course divides students into three categories: poor students, medium students, and excellent students, among which poor students account for 30%, medium students account for 50%, and excellent students account for 20%. (4) The standardization of the education system has brought users a good learning mechanism, in which the teaching resources have been strengthened, and users have very high satisfaction with the evaluation of the whole system.