Secondary Teachers' Self-perceived AI Competences in Relation to Renowned European Digital Competence Frameworks

The fast-paced developments in GenAI technology have begun to change school realities. The aim of this study is to identify what competences teachers of technical subjects are relying on when managing AI use in the classroom and to what degree these competences are covered in the DigComp framework. This study used a qualitative research approach utilizing semi-structured interviews. Nine educators from two vocational upper secondary schools in Austria were interviewed and a thematic analysis of the interviews was conducted to identify competences which were then mapped to DigComp2.2. Results show that several of the AI-related competences identified, such as information literacy and privacy can smoothly be mapped to DigComp2.2. However, other competences such as prompting, and the reflected goal-oriented use of GenAI tools appear not to fit in well and hence point to the necessity of adapting DigComp2.2. Furthermore, the importance of interpersonal skills and a well-founded subject knowledge were highlighted as crucial. This research is targeted at curriculum designers, educators, educational researchers, and administrators. It will also speak to teachers who wish to better deal with and prosper from the emergence of GenAI in schools. Future work will address key factors in developing educators' and students' AI literacy.