Survey Data on Generative AI Use and Perceived Thesis Quality in Higher Education

934 participants (684 students and 250 teachers) were recruited via stratified random sampling across institutional tiers and disciplines. The dataset contains survey results measuring variables like Extent of GenAI Involvement (EX) and Perceived Effect on Thesis Quality (EF), used in a five-step hierarchical regression analysis. It was uploaded by Guangjian Yan on 2026-04-28 under a CC-BY-4.0 license.

Use Cases

• Analyzing the relationship between GenAI engagement and perceived thesis quality based on the EX and EF variables.
• Investigating how institutional tier and discipline moderate the teacher-student evaluation gap based on the described interaction effects.
• Modeling the influence of perceived writing ability development (AB) and attitudes (AT) on thesis quality evaluations.
• Studying the role of institutional policy presence in moderating GenAI use outcomes.

Strengths

• Includes 934 survey responses from a stratified sample across institutional tiers and disciplines.
• Variables are measured using structured scales, supporting quantitative analysis.
• The final hierarchical regression model achieved an R² of .510, indicating a strong explanatory model.

Limitations

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

Provenance

Source

figshare

Collection Method

Stratified random sampling across institutional tiers and disciplines, using structured survey scales.

Time Range

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Freshness

Last updated 2026-04-28 17:50:08; freshness should be verified.

Geography

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