Application and Path Exploration of PDCA Management Model in Higher Vocational Education Management

Abstract

Abstract With the rapid development of society, the total education demand for higher vocational colleges and universities is growing at an extremely fast rate, and the original education management mode can no longer meet the needs of higher vocational education in the new era. The PDCA management model is a continuous improvement model that can achieve the objective of continuous improvement processes and perfectly fits the needs of higher vocational education management. This paper introduces the support vector machine, an algorithm suitable for high-dimensional classification problems, into the PDCA management model to carry out a multidimensional analysis of vocational high school students’ behavioral data, optimizing the checking part of the PDCA management model so that the cycle can continue to play an ideal role. The results of the application of the prediction of academically abnormal students show that the total number of academically normal students is 12,823, the total number of academically abnormal students is 2,981, and the proportion of abnormal students in different schools can be as high as 34.82%, and as low as 12%. The SVM algorithm, in the case of the imbalance between the proportion of academically abnormal and academically normal students, the model is still able to find out the majority of the students with abnormal studies, and it plays a central role in the PDCA management model to make the management of higher vocational education more perfect. By playing a central role, it enhances the management of higher education and creates a unique management path.