Evaluation on the Prospects of School Enterprise Cooperation and the Integration of Industry and Education in Vocational Education in the 5G Era
Zhigang Guo
Philippine Women's University
内容与影响
Talents are the primary resource for the progress of a country and a nation. In the context of the fifth generation mobile communication technology, cultivating high-quality and innovative technical talents is a new task entrusted to vocational colleges by the times. However, many colleges currently lack a mechanism for student employment orientation and ability cultivation, and the cooperation between schools and enterprises is not deep enough, resulting in a disconnect between the cultivation of applied talents in schools and social needs. This article analyzes the problems arising from the cooperation between vocational colleges and enterprises based on the background of the 5G era, and proposes optimization strategies from various aspects such as policies, industry enterprises, and vocational colleges themselves, so as to closely combine industry and teaching and facilitate vocational education to better meet the market demand. By designing comparative experiments, the traditional teaching settings was compared with the way of integrating production and teaching. It was proved that the employment rate of students under the two-way mode of enterprise and education increased by about 11.35%, and enterprises were also more satisfied with this new talent cultivation mode, greatly increasing their enthusiasm for participating in practical teaching and driving the reform and innovation of vocational education. School enterprise cooperation is beneficial for school to increase student employment rates and promote the transformation of talents into skilled ones. Vocational education under the help of 5G must be service-oriented, adhere to the establishment of professional industries, strengthen practical teaching, and create specialized talents urgently needed by the industry and satisfied by all parties to achieve a “win-win situation”.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
回答优先基于摘要、文献信息与可获取全文;依据不足时会明确说明。
学术脉络
学科主题
计算机 / AIAdvanced Technologies in Various Fields
参考文献 2
此处列出前 3 条
施引文献 4
按被引量排序,此处列出前 3 条