Exploring AI competency in Chinese undergraduates through the UNESCO framework

Jue Wang et al.

Acta Psychologica2026https://doi.org/10.1016/j.actpsy.2026.106299article
ABDC A
Weight
0.37

Abstract

Despite China's strategic emphasis on AI education, gaps remain in evaluating undergraduates' competencies and applying international frameworks in this context. The UNESCO AI Competency Framework for Students lacks empirical validation, especially in non-Western settings. This study validates it using survey data from 583 undergraduates across 13 institutions in 9 Chinese cities. We examined four dimensions: Human-centered mindset, Ethics of AI, AI techniques and applications, and AI systems design. Students showed stronger competencies in mindset and ethics than in technical areas. First-years reported higher technical skills than seniors, challenging progression models. Principal component analysis confirmed the four-dimensional structure, with multivariate analyses revealing limited gender and discipline effects, mainly in technical aspects. Findings highlight a theory-practice gap misaligned with national priorities for practical skills. We recommend curriculum reforms via AI co-creation, spiral design, and personalized pathways for responsible AI engagement. This advances theoretical insights and practical guidance for higher education.

1 citation

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1016/j.actpsy.2026.106299

Or copy a formatted citation

@article{jue2026,
  title        = {{Exploring AI competency in Chinese undergraduates through the UNESCO framework}},
  author       = {Jue Wang et al.},
  journal      = {Acta Psychologica},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.actpsy.2026.106299},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Exploring AI competency in Chinese undergraduates through the UNESCO framework

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.