Abstract:

Until a few years ago, teachers were mainly expected to possess strong subject‑matter knowledge, apply effective pedagogical strategies, use technology in instruction, and adapt learning processes to students’ needs. Today, however, these expectations have expanded significantly. With the rapid integration of digital technologies into education—accelerated especially during the pandemic—teachers are now required to adapt quickly, engage with emerging tools, and keep pace with continuous technological change. Although previous research has defined teachers’ technological competencies within various frameworks, the recent and rapid development of artificial intelligence (AI) has reached classrooms and made it necessary to reconsider and redefine teacher competencies for the digital age. Teachers are now expected not only to use technology effectively but also to integrate this knowledge with AI literacy in order to design new and meaningful learning experiences supported by AI tools. In this context, evaluating teachers’ competencies through AI‑adapted models—particularly AI‑TPACK—is essential for understanding their current readiness and for informing future support mechanisms. Moreover, there is a growing need for studies that explore teachers’ knowledge, skills, and pedagogical capabilities specifically related to the use of AI in education. This study aims to examine the AI competencies of high school teachers from different subject areas through the AI‑TPACK framework. The research employed a qualitative design and was conducted with 17 teachers from various regions of Türkiye through four focus group interviews. A semi‑structured interview form guided the data collection, and the analysis was carried out based on the subdimensions of the AI‑TPACK framework. Findings show that teachers generally approach AI with a mix of curiosity and caution, yet demonstrate notable shortcomings across most AI‑TPACK components. These shortcomings are evident in several areas: teachers’ technological knowledge is largely limited to basic familiarity with ChatGPT, with minimal awareness or experience regarding other AI tools; AI is viewed as useful mainly for out‑of‑class tasks such as lesson planning, material development, and question generation, whereas knowledge, strategies, and confidence related to in‑class pedagogical integration remain low; there is no systematic guidance for selecting or adapting AI tools across subject areas; and widespread concerns about ethics, data privacy, and security significantly restrict meaningful integration. Overall, the study reveals that although teachers hold positive intentions toward using AI, they have not yet developed the knowledge, skills, or pedagogical integration capacities required by the AI‑TPACK framework. These findings not only make visible the current state of teachers’ readiness for AI‑enhanced education but also offer a new perspective on how the AI‑TPACK framework functions within a national context—an area still underexplored in the international literature. In this regard, the study provides a data‑driven contribution to global discussions on restructuring teacher education in response to AI and serves as a valuable reference point for researchers examining AI‑driven educational transformation across different systems.

Keywords:

Artificial Intelligence, Teacher Competencies, AI Integration, AI-TPACK.