From Principles to Practice: Development and Validation of a Teacher GenAI Competency Scale

• In Event: AERA Roundtable Session Friday 3:45 pm - Gold 2
  In Roundtable Session: Capacity and Infrastructure for Responsible AI in Education

Abstract

This study developed and validated a scale to assess teachers’ Generative Artificial Intelligence (GenAI) competency. Guided by UNESCO frameworks and empirical evidence, the process involved item generation, expert review, and psychometric testing with data from 560 in-service teachers in China. Exploratory factor analysis identified a 36-item scale with five dimensions: human-centred mindset, ethical and responsible GenAI use, GenAI knowledge and applications, GenAI-enhanced pedagogy, and GenAI-enhanced professional development. Confirmatory factor analysis confirmed the factor structure with excellent model fit, and convergent validity was supported through correlations with a digital competency measure. Descriptive and multivariate analyses examined the effects of demographics. The findings demonstrate the scale’s strong validity and reliability, providing a useful tool for research, policy, and professional development.

Authors

• Xianhan Huang, The Education University of Hong Kong

• Wen SHAO, University of Hong Kong

• Shiyu Zhang, The University of Hong Kong