Lucas, MargaridaZhang, YidiBem-haja, PedroVicente, Paulo Nuno2025-01-142025-01-142024-121360-2357PURE: 106515262PURE UUID: 67298db0-4730-441e-b2f5-6822d4af8373Scopus: 85193591877ORCID: /0000-0002-1952-6016/work/175747469http://hdl.handle.net/10362/177446UIDB/05021/2020 UIDP/05021/2020 UIDB/00194/2020 2021.03379.CEECIND, 2022.14365.BDThis study examines the relation between K-12 teachers’ trust in artificial intelligence (TAI), their knowledge of AI (KAI), and their digital competence (DC). It further examines the relation between TAI and age, sex, teaching experience and International Standard Classification of Education (ISCED) levels. The study employed a comprehensive and validated instrument and used a sample of 211 primary and secondary school teachers. The results show that there is a significant positive relation between all three variables and that KAI is a robust and substantial predictor of TAI. In the absence of KAI, the significant relation between DC and TAI ceases to exist. In addition, teachers with different levels of DC do not show significant differences in their attitudes towards AI. Results further show that TAI is independent of age, sex, teaching experience and ISCED level in this sample of teachers. The study contributes valuable insights into the complex interplay between teachers’ TAI, their KAI, and their DC, providing practical implications for policy, teacher preparation and professional development in the rapidly evolving landscape of AI integration in education.201051038engDigCompEduMachine learningNetwork analysisPrimary and secondary educationProfessional developmentEducationLibrary and Information Sciencesjournal article10.1007/s10639-024-12772-2https://www.scopus.com/pages/publications/85193591877https://link.springer.com/article/10.1007/s10639-024-12772-2