AI-Digital Competency Framework for Teachers, Validated by 44 Experts in Korea

A two-round Delphi study with 44 trained teachers validated a framework of 17 AI-digital competencies across four career stages. The final framework includes 51 behavioral indicators, all demonstrating strong content validity with a Content Validity Ratio of 0.75 or higher. Authored by Ihyeon Yoon and published in March 2026, this 17.3 KB document provides a structured basis for teacher development.

Use Cases

• Designing career-stage-specific teacher training programs based on the 17 validated competencies.
• Developing diagnostic tools for teacher competency assessment using the framework's 51 behavioral indicators.
• Analyzing differences in competency priorities between early-career and experienced teachers based on the study's ANOVA results.
• Informing national or institutional policy for AI in education using the career-responsive framework structure.

Strengths

• Framework validated through a formal two-round Delphi study involving 44 expert teachers.
• All 51 behavioral indicators achieved a Content Validity Ratio (CVR) of 0.75 or higher, indicating strong expert consensus.
• Analysis includes statistical tests (ANOVA with Scheffé post-hoc) to identify significant differences across four defined career stages.

Limitations

• The dataset is a 17.3 KB DOCX file describing the framework; the underlying validation data (e.g., raw survey responses) is not included.
• Row count and column-level documentation for any underlying data are unknown.
• Geographic focus is specifically on in-service teachers in Korea, which may limit generalizability.

Provenance

Source

figshare, authored by Ihyeon Yoon.

Collection Method

Developed from national policies and global standards, then validated via a modified Delphi study.

Freshness

Last updated 2026-03-18 06:42:25.

Geography

Korea (in-service teachers)