Empirical Research on the Construction of Labor Education Scenarios in Higher Vocational Education Empowered by Artificial Intelligence and Its Learning Outcomes
Year: 2026
Type: conference-paper
Study design: Clinical Trial
Abstract: Under the background of the in-depth advancement of the national strategies for digital transformation in education and artificial intelligence, problems such as the disconnection between higher vocational labor education and the demands of industrial digitalization, the superficial application of technology, and the lack of quantitative analysis of educational outcomes have become prominent. This paper, with computer engineering technology as the core support, integrates key technologies in the field of computer science such as artificial intelligence, big data analysis, virtual reality/digital twins, and Internet of Things perception, to construct an intelligent scene system for higher vocational labor education based on multi-modal data collection and intelligent decision-making. It focuses on designing a full-process technical architecture driven by computer technology for the perception layer, decision-making layer, and interaction layer, and proposes a personalized teaching strategy optimization model centered on hierarchical reinforcement learning algorithms. The research takes students majoring in artificial intelligence technology application in higher vocational colleges as the subjects and conducts a 12-week controlled experiment. Through computer vision and data mining technologies, over 8,000 sets of practical operation data and interaction behavior data during the labor process are collected. The learning outcomes are quantitatively analyzed from dimensions such as labor skills, innovative practice, and digital literacy. The experimental results show that the labor education scene based on the in-depth application of computer technology can increase the standardization of students' labor skills operation by 42.3%, the implementation rate of innovative solutions by 58.6%, and the operational efficiency of digital tools by 39.5%. It provides empirical data support for the engineering application of computer technology in vocational education, and also creates a feasible and replicable technical solution and practical path for the digital transformation of labor education in higher vocational colleges.
Author: Lajiao Wang
Institution: Shantou Polytechnic
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7223889376