Self-regulated learning and technological integration competency: A multilevel latent profile analysis of preschool teachers

Abstract

Existing research has independently examined teachers' beliefs, emotions, and knowledge related to technology use, but few studies have explored how these components can be combined to form technological integration competency (TIC). Furthermore, the role of self-regulated learning (SRL) in predicting TIC remains underexplored. This study employed multilevel latent profile analysis (MLPA) to identify TIC profiles at both teacher and school levels and examineed their associations with continuous usage intention and technology-enabled productivity. Using data from 3256 teachers nested within 274 schools, single-level latent profile analysis revealed three teacher profiles: Novice, Competent, and Advanced. Teachers in more advanced profiles exhibited higher usage intention and reduced productivity. At the school level, three profiles, Developing, Progressing, and Leading, were identified based on the distribution of teacher profiles, with substantial differences in school-level usage intention and productivity. SRL emerged as a significant predictor of TIC profiles at both levels, with higher SRL increasing the likelihood of teachers and schools belonging to better profiles. The discussion emphasizes integrating beliefs, emotions, and knowledge into teacher training programs to promote TIC while considering the Chinese cultural context.