Profiling Preschool Teachers' Readiness for AI-Enhanced Professional Development: A Diagnostic Framework Based on Digital Literacy

Abstract

The integration of artificial intelligence (AI), particularly generative AI, is transforming teacher professional development (PD) into a continuous, AI-mediated learning process. However, the effectiveness of AI-enhanced PD depends on teachers' readiness to engage with AI as a professional learning partner. This study develops and validates the preschool teachers' digital literacy scale as a diagnostic framework for assessing readiness for AI-enhanced PD among preschool teachers in China. Using data from 658 teachers nationwide, exploratory and confirmatory factor analyses supported a 5-D structure encompassing digital awareness, technical capability, pedagogical application, social responsibility, and PD orientation. Latent profile analysis identified three readiness groups—Emerging (13.37%), Progressing (46.20%), and Proficient (40.43%)—revealing a structural imbalance characterized by strong ethical awareness but comparatively weaker technological capability across profiles. The findings indicate that AI-enhanced PD should not be uniformly designed and instead requires differentiated, staged approaches aligned with teachers' readiness profiles. By positioning diagnostic profiling as an entry point for adaptive AI-supported PD design, this study offers scalable implications for early childhood education and AI-driven professional learning reform.