Evolutionary Trends and Structural Characteristics of Chinese Vocational Computer Curricula in the AI Era: A Semantic Network Analysis

The rapid advancement of Artificial Intelligence (AI) has driven significant changes in vocational computer curricula in China. Unlike previous studies focused on theoretical models, this research uses a data-driven approach to evaluate the structural evolution of these reforms within the Chinese vocational education context. Utilizing the Word2Vec model and semantic network analysis, we examined 370 core academic papers published between 2018 and 2025. The empirical results reveal three critical structural characteristics. First, we identify a distinct structural stratification in curriculum integration, where application-layer courses demonstrate high semantic coupling with AI, whereas infrastructure-layer courses remain relatively isolated. Second, we observe a pragmatic turn in the temporal evolution of reform focus; post-2022, the discourse decisively shifted from macroscopic policy design to microscopic pedagogical practice. Third, we detect a pronounced asymmetry in stakeholder attention, characterized by a heavy concentration on technological tools and student outcomes, contrasted with the marginalization of teacher digital literacy. These findings highlight the need to strengthen foundational courses and enhance faculty capabilities for a more balanced educational structure.