DOI: 10.1177/09504222261478197 ISSN: 0950-4222

Bridging the gap between vocational AI curricula and industry skill demand: Evidence from China

Huixiang Xiao, Hoi Leong Lee, Kaige Zheng, Zhuoting Kuang, Qi Wei Oung, Qian Zhang

China’s rapid artificial intelligence (AI) expansion has intensified demand for graduates who combine applied technical skills with professional competencies. This study examines the alignment between vocational AI curricula and employer skill demand using 498,331 job advertisements from 2020 to 2024 and 46 institutional training plans. We develop a bilingual taxonomy of 198 hard- and soft-skill keywords and calculate a demand-weighted coverage index, supported by bootstrap, permutation and robustness checks. Results indicate a selective technology lag: programming and AI practicum courses align relatively well, while cloud computing and big-data competencies remain less visible in curricula. Soft-skill coverage is also uneven, with many professional attributes implicit rather than systematically embedded. Work-integrated learning shows the strongest overall alignment, suggesting that practicums, internships and capstone projects are key mechanisms for curriculum renewal.

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