Heterotrait-Monotrait Ratio (HTMT): AI Literacy Survey of 319 Ghanaian Teachers

Heterotrait-Monotrait Ratio (HTMT) data from a cross-sectional survey of 319 basic school teachers in Ghana, authored by Valentina Arkorful and last updated in April 2026. The dataset supports analysis of AI literacy across four dimensions: knowledge, application, evaluation, and ethics.

Use Cases

• Analyzing relationships between AI knowledge, application, and ethics based on the four key literacy aspects.
• Benchmarking AI literacy levels among teachers in a specific geographic context based on the Ghanaian sample.
• Validating structural equation models for educational constructs using the provided HTMT ratios.
• Informing the design of teacher professional development programs based on identified literacy dimensions.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Data collection from 319 teachers provides a specific sample size.
• Focus on four defined AI literacy dimensions (knowledge, application, evaluation, ethics) provides a clear conceptual structure.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• The dataset is very small at 5.5 KB, indicating limited scope.
• Data may reflect geographic and occupational bias inherent to the Ghanaian teacher sample.

Provenance

Source

figshare, authored by Valentina Arkorful.

Collection Method

Cross-sectional survey design using purposive sampling.

Time Range

null

Freshness

Last updated 2026-04-17 17:37:45.

Geography

Ghana