Construction of vocational undergraduate education teacher team based on deep learning

3Citations
Citations of this article
40Readers
Mendeley users who have this article in their library.

Abstract

With the rapid development of vocational undergraduate education, the construction of teachers is very important to improve the quality of education and train outstanding talents. This study takes deep learning as the theoretical basis to explore the construction of vocational undergraduate education teacher team based on deep learning. Through comprehensive literature review, quantitative research methods and questionnaire design, the current situation of vocational undergraduate education teachers is deeply analyzed, and the application potential of deep learning in teacher training is discussed. The research results show that deep learning can provide new teaching tools and techniques to promote the professional development of teachers and improve teaching effectiveness. However, there are also some problems and challenges in practical application, such as teachers' cognition and application level of deep learning need to be improved. Therefore, this study puts forward some strategies to solve these problems, and looks forward to the future development of vocational undergraduate education teacher team construction.

Cite

CITATION STYLE

APA

Tang, H. (2024). Construction of vocational undergraduate education teacher team based on deep learning. Journal of Computational Methods in Sciences and Engineering, 24(1), 201–216. https://doi.org/10.3233/JCM-237041

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free