Expert Consensus on Ethical AI Governance in Higher Education

A Delphi study involving 31 experts from higher education institutions in China and Malaysia, conducted in 2026. It identifies and ranks six key dimensions for the ethical governance of generative artificial intelligence in academic settings. The study achieved a statistically significant level of expert consensus (Kendall’s W = 0.248, p = .001).

Use Cases

• Designing institutional AI governance policies based on the six identified dimensions.
• Developing faculty training programs based on the 'GAI Literacy, Training, and Capacity Building' dimension.
• Creating technical and data privacy safeguards based on the 'Technical Safeguards, Data Privacy, and Fairness' dimension.
• Framing academic integrity guidelines based on the 'Academic Integrity and Ethical Accountability' dimension.

Strengths

• Based on a three-round Delphi method with 31 expert participants.
• Achieved a statistically significant level of expert consensus (Kendall’s W = 0.248, p = .001).
• Identifies and ranks six specific, actionable dimensions for ethical governance.

Limitations

• The dataset is a 53.5 KB document, indicating a limited scope focused on study findings rather than raw data.
• Row count and column-level documentation are absent; the content is a qualitative analysis.
• The data reflects expert opinion from a specific geographic context (China and Malaysia).

Provenance

Source

Zhikai Yang via figshare.

Collection Method

A three-round Delphi study with qualitative analysis and expert ranking.

Time Range

Study conducted in 2026.

Freshness

Last updated 2026-06-02 09:20:09.

Geography

Expert participants from higher education institutions in China and Malaysia.