Integrating AI in Education: An Analysis of Factors Influencing the Acceptance, Concerns, Attitudes, Competencies and Use of Generative Artificial Intelligence Among Polish Teachers

Abstract

This paper presents the results of a survey on the use of artificial intelligence (AI) among teachers in Poland (N=289). The survey, conducted in December 2024 and January 2025, used the extended educational technology acceptance model (EETAM) to capture factors supporting and blocking the integration of AI in education (primary and secondary schools). The aim of the study is to identify factors influencing the acceptance and use of AI tools by teachers in their professional work. Based on the EETAM, the relationships between perceived usefulness, ease of use, digital competence, AI-related concerns, attitudes, intention to use and actual use of AI are analysed. This study is unique in that it fills a local empirical gap (based on EETAM assumptions) on AI usage patterns among teachers. Cluster analysis revealed three groups of teachers: (1) intensive users of AI (13.5%), (2) occasional users (30%) and (3) nonusers (43.5%). The results indicate that the most frequently used functions of AI are information retrieval and text translation, while more advanced applications remain marginally used in educational contexts. In turn, structural modelling confirmed the key role of perceived usefulness and digital competence in shaping intentions to use AI, which in turn have a strong influence on actual use. Perceived ease of use had a moderate impact on usability, while anxiety relating to AI appeared to be of minimal importance. The overall model explained 72% of the variance in intention to use AI and 30% of actual use, highlighting the high effectiveness of the research approach adopted. The results highlight the need to further improve teacher education programmes in the context of AI use, especially with regard to the development of teachers’ digital competences, as well as to strengthen positive attitudes towards AI, also by emphasising the praxeological nature of the solutions analysed.