AI Literacy and Appropriateness Judgments of Postgraduate Researchers in China

A mixed-methods study from a Chinese higher education context contains quantitative survey data from 126 participants and qualitative interview transcripts from 19 participants. The data investigates postgraduate researchers' AI literacy and their appropriateness judgments of generative AI use across five stages of academic writing. The dataset was authored by Jin, Shan and last updated on 2026-05-19.

Use Cases

• Analyzing correlations between AI literacy scores and appropriateness judgments based on the AI Literacy Scale and Appropriateness Judgement Scale.
• Studying qualitative themes on generative AI use in academic writing from member-checked interview transcripts.
• Comparing AI literacy perceptions between master's and doctoral students in a Chinese university context.
• Investigating contextual factors influencing AI tool appropriateness across different stages of the writing process.

Strengths

• Includes both quantitative (N=126) and qualitative (N=19) data from a mixed-methods study.
• Interview transcripts are described as anonymised and member-checked.
• Focuses on a specific population: master's and doctoral students at a comprehensive university in China.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the quantitative data is unspecified beyond the participant count.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

dataverse

Collection Method

Mixed-methods study using surveys and interviews.

Freshness

Last updated 2026-05-19 09:31:05; freshness should be verified.

Geography

China