Digital innovations in higher education management and mechanisms for high-quality training of students

Abstract

With the rapid development of modern information technology, the management mode and cultivation path of higher education have undergone great changes, and this paper explores this change from digital innovation. First of all, this paper analyzes the mechanism of education management and student training in higher education and puts forward the digital innovation path of higher education management and student training in combination with education big data. Then, on the basis of the traditional Apriori algorithm, the AHP-DEMATEL method is introduced for empowerment, and weighted ordered directed constraint Apriori algorithm is proposed for data mining, and the PSO-LS-SVM prediction model is proposed for data prediction by combining particle swarm algorithm for optimization under least squares support vector machine algorithm. Finally, the data on educational management and the effects of student cultivation and innovation on students are mined and predicted, and the relationship between the two is explored. The results show that the improved Apriori algorithm ends up with the number of rules around 20 when the support degree is 0.22, the confidence degree is 0.50, and the interest degree is 0.80, and the relative errors of the prediction are all under the level of 0.03, and the average relative error of the data of the experimental results is 78, and the innovation scores are all above 80. Higher education management and the digital innovation of students’ high-quality training mechanisms show a positive correlation, which can promote the overall development of students.

Keywords

• apriori algorithm
• ahp-dematel method of empowerment
• support vector machine
• pso-ls-svm predictive model
• educational management
• 97u10