Work

Construction of a Dynamic Optimization Model for Vocational Education Program Alignment in the Context of New Quality Productive Forces

Year: 2025

Type: conference-paper

Abstract: Addressing the industrial transformation challenges driven by the development of New Quality Productive Forces (NQPF), this paper constructs a data-driven dynamic optimization model for vocational education program alignment. The model establishes a skill demand sensing system through multi-source data fusion, employs a hybrid algorithm combining the Grey Prediction Model and BP Neural Network to forecast skill demand trends, introduces knowledge graph technology to build dynamic mappings between programs and industries, and designs a feedback control mechanism to achieve continuous optimization of program alignment. Validation results from a case study on an intelligent manufacturing program cluster demonstrate that the model can improve the alignment between programs and industries by 40%, providing an effective decision-support tool for vocational education to precisely serve the development of NQPF.

Source: International Conference on Artificial Intelligence and Sustainable Development

DOI: 10.1145/3786484.3786519

Authors: Weixuan Li, Yun Mo, Pingping Wei

Institutions: Qinhuangdao Vocational and Technical College, Capital Normal University

Language: English

Topic: Vocational and Entrepreneurial Education

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDGs: Decent work and economic growth, Industry, innovation and infrastructure, Quality education

Open Access status: hybrid

OpenAlex ID: W7127601030

FWCI: 2.985

Cites: 2

Cited by: 1

Related to: 10