Academic Opinions on AI in Higher Education from a Turkish University

A 2026 Q-methodology study by Hıdır Polat examines the subjective perceptions of 25 academics from a Turkish state university regarding AI integration. The analysis of a 40-item Q-set identified three principal factors explaining 53% of the variance, representing cautious, techno-optimistic, and pessimistic viewpoints. The dataset includes the raw Q-sort data and analysis results.

Use Cases

• Analyze polarization in academic perspectives on AI based on the three identified principal factors (cautious, techno-optimistic, pessimistic).
• Study the consensus on ethical frameworks for technological transformation in higher education based on the described findings.
• Replicate or extend the Principal Component Analysis (PCA) and Varimax rotation on the provided 40-item Q-set data.
• Investigate correlations between academic discipline and AI perception using the purposive sampling of 25 academics across various fields.

Strengths

• Includes a 40-item Q-set developed from a literature review and expert opinions.
• Analysis explains 53% of the total variance through three distinct factors.
• Data is based on responses from 25 academics selected via purposive sampling.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data reflects a specific geographic and institutional bias, being from a single state university in Turkey.

Provenance

Source

Hıdır Polat via figshare

Collection Method

Q-methodology study using a structured 40-item Q-set, analyzed with Principal Component Analysis (PCA) and Varimax rotation.

Freshness

Last updated 2026-04-13 22:02:15

Geography

A state university in Turkey