Survey of Chinese University Faculty Generative AI Use, 365 Respondents

365 faculty members from two universities in China completed an online survey investigating their Generative AI use. The dataset likely contains survey responses measuring task values, perceived costs, self-efficacy, behavioral intention, and usage frequency. The data was uploaded by Peng Sun on figshare in April 2026 under a CC-BY-4.0 license.

Use Cases

• Analyze relationships between self-efficacy and Generative AI usage frequency based on survey constructs.
• Model the influence of utility value on behavioral intention to use Generative AI.
• Compare the predictive power of intrinsic, attainment, and utility task values on adoption outcomes.
• Study the role of perceived costs in faculty technology adoption decisions.
• Validate expectancy-value theory constructs in a Generative AI context within higher education.

Strengths

• Survey data from 365 faculty members provides a substantial sample size.
• The dataset is structured around validated psychological constructs (expectancy-value theory).
• The study employed structural equation modeling, suggesting rigorous statistical analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (35.2 KB), indicating limited scope or complexity.

Provenance

Source

figshare

Collection Method

Online survey administered to faculty members.

Freshness

Last updated 2026-04-24 05:40:02; freshness should be verified.

Geography

China