Professional Development of Preservice Teachers in Artificial Intelligence (AI): Empirical Evidence from a Theory- and Practice-Based Seminar

Abstract

Due to the rapid rise of artificial intelligence (AI), teacher professionalism needs to be rethought. Teachers require a deep understanding of the technical, ethical and pedagogical aspects of AI and how AI changes teaching and learning. This study examines teacher education students’ knowledge of AI as well as their attitudes towards its use in schools. It also explores the potential of a university seminar on AI in education to promote a professional approach and build foundational AI competencies among future teachers. To this end, a pre-post mixed-methods design was employed with a sample of 45 teacher education students who attended a seminar on AI during the final phase of their initial teacher training. Qualitative content analysis was applied to analyze to gain insights into individual perspectives on AI, particularly in educational contexts – supplemented by descriptive statistics on self-rating items. The findings indicate positive attitudes towards the use of AI, but reveal limited knowledge, both about the basics of AI and its application in schools. The study demonstrates that a seminar combining theory and practice can effectively develop AI-related competencies and support a critically reflective approach to digital technologies in education. The study therefore contributes to the emerging body of literature on AI in the context of teacher education, addressing a notable gap in this field.