Chinese University Faculty Generative AI Use Survey, 365 Respondents

A survey of 365 faculty members from two Chinese universities collected by Peng Sun. It measures behavioral intention and frequency of Generative AI use, predicted by task values, perceived costs, and self-efficacy. The data was last updated on 2026-04-24.

Use Cases

• Modeling technology adoption intention based on utility value and self-efficacy constructs.
• Analyzing the relationship between perceived costs and actual usage frequency of Generative AI.
• Comparing the predictive power of intrinsic, utility, and attainment task values for behavioral outcomes.
• Designing professional development programs for educators based on key motivational factors.

Strengths

• Survey data from 365 faculty members provides a substantive sample size.
• Analysis uses structural equation modeling, suggesting a rigorous statistical approach.
• Dataset is openly licensed under CC-BY-4.0 for reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is limited to faculty from two universities in China, which may affect generalizability.

Provenance

Source

Peng Sun via figshare.

Collection Method

Online survey administered to faculty members.

Freshness

Last updated 2026-04-24 05:40:04; freshness should be verified.

Geography

China (two universities).