Work

Employment skill reconstruction for higher vocational artificial intelligence application students under AI technology evolution: A machine learning-based empirical study

Year: 2026

Type: article

Abstract: This study investigates employment skill reconstruction for higher vocational students majoring in artificial intelligence applications under AI-driven technological transformation. A hybrid framework combining questionnaire analysis and machine learning was proposed using 547 valid samples. Four predictive models were developed, among which XGBoost achieved the highest accuracy (93.2%). Results indicate that AI tool usage, prompt engineering, and project experience are the most critical factors affecting employability. An AI-driven skill reconstruction framework is proposed to support vocational curriculum reform.

Source: Advanced Electromagnetics

DOI: 10.7716/aem.v15i3.4211

Authors: X. Huang, L. J. Deng

Institutions: Chongqing Vocational and Technical University of Mechatronics, Chongqing Hailian Vocational Technical College

Language: English

Topic: Higher Education and Employability

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDGs: Quality education, Decent work and economic growth

Open Access status: diamond

OpenAlex ID: W7204115371

FWCI:

Cites: 14

Cited by:

Related to: 10