<p>Core Dimensions of the Questionnaire Scale.</p>

Yixuan Zeng's dataset contains questionnaire data from an empirical study on Generative AI (GAI) in higher education. It includes 207 valid responses from Chinese university students, analyzed via structural equation modeling to examine behavioral mechanisms. The data was last updated on 2026-04 28 and is shared under a CC-BY-4.0 license.

Use Cases

• Modeling the relationship between role adaptation, self-efficacy, and AI-assisted learning behaviors based on the described triadic framework.
• Analyzing the impact of institutional support and task-technology fit on student exploration and exploitation behaviors mentioned in the description.
• Investigating the correlational pathways between exploitation/exploration behaviors and learning outcomes as described in the study.

Strengths

• Dataset is based on 207 valid questionnaire responses, providing a defined sample size.
• The underlying study model demonstrates good fit and significant path relationships among variables, as reported.
• Data is shared under a permissive CC-BY-4.0 license, facilitating reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain modeling tasks.
• The study authors note the results reflect correlational evidence and do not establish a causal mechanism.

Provenance

Source

Yixuan Zeng via figshare

Collection Method

Questionnaire survey of Chinese university students, analyzed via structural equation modeling.

Time Range

null

Freshness

Last updated 2026-04-28 17:42:00; freshness should be verified.

Geography

Likely China, based on the participant description of Chinese university students.