Research on Optimizing Vocational Education Curriculum System through Machine Learning to Enhance Students’ Employability

Yumin Wang 1
1Department of Economic Management, Luohe Institute of Technology, Henan University of Technology, Luohe, Henan, 462002, China

Abstract

In today’s deepening education reform, promoting the deep integration of technology and education has facilitated the process of informatization of school education. Vocational education shoulders the important responsibility of cultivating “high-quality laborers and technical talents”, and the reform of informatization of vocational education has gradually become the focus of attention. In this study, we construct a prediction model of learning achievement based on machine learning to optimize the vocational teaching curriculum system. In this paper, before constructing the prediction model, the basic information data and learning behavior data of students are firstly subjected to feature extraction and feature selection. Then CNN combined with BiLSTM and Attention is used to construct the student performance prediction model CNN-BiLSTM-Attention. Finally, based on the performance prediction model, this study proposes the optimization path of the vocational education curriculum system to solve the problem of student employment. The model in this paper achieved the best prediction results in the performance comparison with both the single model and the integrated model, and the indicators were 0.961, 0.953, 0.985, 0.966, and 0.957, respectively. Moreover, it was found that the model had better prediction results in the process of vocational education courses at 80% and above. Among the features, the importance of the relevant features about honor acquisition is higher, all of them are above 0.8, which is an important factor affecting students’ performance. In the actual application of grade prediction, only one student had only 61.6 points in the final semester’s grade prediction, which had the risk of not being able to successfully graduate and proceed to employment. The study shows that the prediction model based on machine learning in this paper has good performance and can provide a strong basis for the reform and optimization of the vocational education curriculum system and promote the informatization process of vocational education.

Keywords: machine learning, CNN-BiLSTM-Attention, performance prediction model, vocational education, curriculum system optimization