AIGC Adoption Survey of 609 Chinese Design Students via Extended UTAUT

Ru Zhang collected 609 survey responses from Chinese design students in 2026 to study AIGC adoption factors using an extended UTAUT model. The data consists of two independent waves (376 and 233 records) measuring demographics and psychological constructs via 5-point Likert scales. It specifically targets students with prior experience using AIGC tools for design assistance.

Use Cases

• Modeling the relationship between 'AI ethical anxiety (AEA)' and 'behavioral intention (BI)'
• Testing the influence of 'job creativity requirement (JCR)' on AIGC adoption
• Segmenting 'perceived ethical risks (PER)' by 'education level' or 'major'

Strengths

• 609 total valid responses across two independent survey waves for validation
• 9 theoretical constructs measured including niche variables like AI ethical anxiety
• IRB-approved collection from a specialized demographic of design students

Limitations

• Geographic bias limited to higher-education students in China
• Column headers and item text are in the original Chinese language
• Potential self-reporting bias inherent in online survey data

Provenance

Source

Humanities & Social Sciences Communications Dataverse

Collection Method

Online survey via Wenjuanxing platform

Freshness

Last updated February 2026

Geography

China