K-12 Teacher Survey on Digital Competence and Attitudes Toward Generative AI

352 K-12 teachers from a large urban school district in Indonesia participated in a quantitative survey assessing four constructs: General Digital Competence, AI-Specific Competence, Teacher Self-Efficacy for AI Integration, and Attitudes Toward Generative AI in Education. The dataset, authored by Emmanuel Nana Kwesi Ofori Darko and last updated in May 2026, contains results from a correlational study, with the hierarchical regression model explaining 62% of the variance in teachers' attitudes.

Use Cases

• Correlational analysis between teacher self-efficacy and attitudes toward AI based on the four measured constructs.
• Regression modeling to predict teacher attitudes using competence and self-efficacy scores as described in the study.
• Comparative studies on AI adoption readiness across different teacher demographics mentioned in the description.

Strengths

• Dataset includes responses from 352 K-12 teachers, providing a specific sample size.
• The hierarchical regression model explained 62% of the variance in the target variable, as reported in the results.
• Correlation coefficients for all variables are provided, with the strongest being r=0.75 between TSE-AI and ATGAI-E.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is from a single urban district in Indonesia, which may limit generalizability.

Provenance

Source

figshare

Collection Method

Online questionnaire survey of K-12 teachers.

Freshness

Last updated 2026-05-26 11:53:02; freshness should be verified.

Geography

Large urban school district in Indonesia.