AI literacy in Chinese nursing students: ethics weakest domain

A cross-sectional study of Chinese nursing students examined their level of artificial intelligence literacy and what shapes it. Overall literacy was moderate but uneven, with the ethics dimension scoring lowest while operational skills were stronger.

Key factors linked to higher literacy included how often students used AI, their attitudes toward AI, interest in AI, and general digital literacy. Specific subdomains showed different associations, such as gender with awareness and ethics, and age with usage.

What the study examined

This study measured the level of artificial intelligence literacy among nursing students in a Chinese higher education program and explored what factors are associated with that literacy. The research aimed to identify which parts of literacy were stronger or weaker and which student characteristics or behaviors related to those differences.

Data were gathered through anonymous, self-administered online questionnaires and analyzed using descriptive statistics and multivariable regression to look for associations between literacy scores and potential determinants.

Key findings

The overall literacy level observed was moderate but uneven across different dimensions. Students scored highest on operational usage skills and lowest on ethics related to artificial intelligence.

• Overall score: The sample showed a moderate mean score on the literacy scale, indicating room for growth.
• Weakest domain: Ethics was the least developed area of competence.
• Stronger domain: Practical, operational usage performed better than ethical understanding.

Several factors were significantly associated with higher literacy. Frequency of AI use, positive attitudes toward AI, and stronger digital literacy were important predictors. Interest in AI also played a role in shaping literacy profiles.

• Awareness correlated with gender, attitudes toward AI, interest in AI, and digital literacy.
• Usage correlated with age, frequency of AI use, and attitudes toward AI.
• Evaluation correlated with attitudes toward AI.
• Ethics correlated with gender.

Why it matters

Findings highlight gaps in readiness for tech-driven healthcare, especially in ethical understanding. The pattern of associations suggests that both experience with tools and underlying attitudes and digital skills shape how prepared students are.

The results point toward educational priorities such as targeted ethics education and digital skills development to strengthen preparedness for environments where these technologies are integrated into clinical, educational, and research settings.

By identifying which domains are weaker and what predicts stronger literacy, the study offers a basis for designing focused curricula and workshops to address specific needs within nursing education.