Study on the Transformation and Innovation Strategy of Labor Education in the Era of Artificial Intelligence
Year: 2025
Type: article
Abstract: As an important engine for the development of new quality productivity, artificial intelligence has triggered the transformation of industry enterprises, employment and career structure, and put forward new requirements for talents and education. These changes have undoubtedly become a realistic demand for the transformation and development of labor education. However, there are still many deficiencies in the current labor education in terms of educational philosophy, curriculum system, teaching content and methods, teaching staff, evaluation mechanism, etc., which are difficult to meet the needs of the artificial intelligence era. In order to explore the transformation and innovation strategies of labor education in the era of artificial intelligence, this study comprehensively uses the methods of literature, induction, and deduction, and systematically sorts out the objective demands of labor education reform in the era of artificial intelligence through theoretical analysis and case studies, and puts forward specific implementation paths, including: establishing the concept of labor education in the era of artificial intelligence, constructing the curriculum content of labor education in the era of artificial intelligence, building a teaching team that meets the needs of labor education in the era of artificial intelligence, exploring new teaching methods based on artificial intelligence and improving the evaluation mechanism of labor education empowered by artificial intelligence. These strategies have important theoretical and practical value for promoting labor education to meet the needs of the era of artificial intelligence, expanding its connotation and extension, and improving its quality and effect.
Source: Education Study
DOI: 10.35534/es.0705104
Authors: Zhao Bingchuan, Wang Quanwang
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411289724