K-12 Teacher Survey on Digital Competence and Attitudes Toward Generative AI
by Emmanuel Nana Kwesi Ofori Darko·Updated 10d ago
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Description
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.
Primary data file is a 17.7 KB DOCX document, which may require conversion for analysis.