Constructing The "Five in One" Talent Training Mode Based on Digitalization
- DOI
- 10.2991/978-94-6463-040-4_124How to use a DOI?
- Keywords
- Digitalization; Five-in-one; Analytic hierarchy process; Talent cultivating mode
- Abstract
The deep integration of digitalization and education is the inevitable trend of educational development. Under the influence of the digital wave, the talent training mode of higher vocational education is facing great challenges, and it is urgent to carry out the digital transformation of education. The construction of digital talent training mode is the only way to deepen the reform of teaching mode and improve the quality of talent training. This paper analyzes the current situation of talent training mode, constructs a talent training quality model by using analytic hierarchy process, quantitatively analyzes the influencing factors of talent training quality, and constructs a five in one talent training mode based on digitalization, which is "value guidance, cultural inheritance, knowledge impartment, skill training and quality cultivation", in order to provide reference for improving the quality of talent training and promoting the digital transformation of higher vocational education.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yuncheng Li PY - 2022 DA - 2022/12/27 TI - Constructing The "Five in One" Talent Training Mode Based on Digitalization BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 817 EP - 822 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_124 DO - 10.2991/978-94-6463-040-4_124 ID - Li2022 ER -