A profile analysis of pre-service teachers’ AI acceptance: Combining behavioral, technological, and human factors - Zhang, Chengming; Hu, Min; Wu, Weidong; Chen, Yanfen; Kamran, Farrukh; Wang, Xining (Teaching and Teacher Education, 2025)
This study aims to identify distinct profiles of AI acceptance among pre-service teachers. Latent profile analysis and ANOVAs were conducted to determine whether homogeneous latent profiles exist within a sample of 453 pre-service teachers in China. Our findings revealed four different profiles: High Acceptors (19.21 %), Cautious Supporters (54.30 %), Skeptics (16.56 %), and Pragmatic Adopters (9.93 %). Additionally, the findings indicate that all groups express concern about AI-related technological factors. More specifically, the results point out the importance of AI compatibility and factors related to digital literacy in shaping AI acceptance among pre-service teachers across different groups.
CRIS-Team Scopus Importer:2025-05-30
Keywords: AI acceptance; Latent profile analysis; Pre-service teachers; Technology acceptance model