Exploring AI competency in Chinese undergraduates through the UNESCO framework.

Area of Science:

• Higher Education
• Artificial Intelligence Education
• Educational Assessment

Background:

• China prioritizes AI education, yet lacks validated frameworks for assessing undergraduate AI competencies.
• International frameworks, like UNESCO's AI Competency Framework for Students, require empirical validation in diverse, non-Western contexts.

Purpose of the Study:

• To empirically validate the UNESCO AI Competency Framework for Students within the Chinese higher education system.
• To assess undergraduate AI competencies across four key dimensions: mindset, ethics, techniques, and design.

Main Methods:

• Survey data collected from 583 undergraduates across 13 institutions in 9 Chinese cities.
• Validated the UNESCO framework using Principal Component Analysis and multivariate analyses.
• Examined AI competencies across four dimensions: Human-centered mindset, Ethics of AI, AI techniques and applications, and AI systems design.

Main Results:

• The four-dimensional structure of the UNESCO framework was confirmed.
• Students demonstrated stronger competencies in human-centered mindset and AI ethics compared to AI techniques and systems design.
• First-year students reported higher technical skills than seniors, contrary to typical academic progression models.
• Limited effects of gender and academic discipline were observed, primarily in technical AI aspects.

Conclusions:

• A significant theory-practice gap exists, with AI education in China not fully aligning with national priorities for practical skill development.
• Curriculum reforms, including AI co-creation, spiral curriculum design, and personalized learning pathways, are recommended for responsible AI engagement.
• The validated framework offers theoretical insights and practical guidance for enhancing AI education in higher institutions globally.