Model Summary: Survey on Generative AI Use in Undergraduate Thesis Work

A 2026 study by Guangjian Yan surveyed 934 participants (684 students and 250 teachers) on Generative AI use in undergraduate thesis work. The dataset contains results from structured scales measuring variables like Extent of GenAI Involvement and Perceived Effect on Thesis Quality. It is stored in an XLS file and shared under a CC-BY-4.0 license.

Use Cases

• Analyze the relationship between GenAI involvement and perceived thesis quality based on the measured variables.
• Investigate differences in teacher and student evaluations across institutional tiers and disciplines.
• Model the moderating effects of policy presence on attitudes toward GenAI use.
• Examine the association between perceived writing ability development and evaluations of thesis quality.

Strengths

• Includes 934 survey participants, stratified across institutional tiers and disciplines.
• Variables were measured using structured scales, suggesting a standardized collection method.
• The analysis employed hierarchical regression, indicating a structured analytical approach.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The data is cross-sectional and self-reported, capturing perceived rather than objective quality.

Provenance

Source

Guangjian Yan

Collection Method

Data was gathered via a survey using a stratified random sampling method across institutional tiers and disciplines.

Time Range

2026

Freshness

Last updated 2026-04-28 17:50:07; freshness should be verified.

Geography

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