Mapping of Ai-related Competences in Educators

Abstract Book of the 9th World Conference on Research in Teaching and Education

Year: 2025

[PDF]

Mapping of Ai-related Competences in Educators

Oliver Schulz, Christof Imhof, René Schumann, Dario Zenhäusern, Aron Oggier, Per Bergamin

ABSTRACT:

In contemporary education, students and teachers face pressing challenges in increasingly AI-driven learning environments, ranging from responsibly handling sensitive data to integrating AI-based tools. Meeting these demands requires new, clearly defined competences. While AI-related teaching competences have recently gained attention in research and practice, their structure, predictors, and reliable assessment remain underexplored. In this study we developed and validated a self-report instrument to assess AI-related competences in educators, introducing a novel multi-dimensional approach (attitude, knowledge, skills, and behavior) across six competence areas. Data was collected from 170 higher education teachers and 154 pre-service teachers in Switzerland. Statistical analysis demonstrated satisfactory reliability and validity of the proposed tool. Practicing teachers reported higher competence levels than pre-service teachers in almost all areas and dimensions, supporting known-groups validity. Moreover, competence levels were associated with external factors such as institutional resources, educational level, teaching level, and disciplinary background, with STEM teachers reporting the highest competence levels. Finally, while teachers expressed a highly positive attitude towards AI, their comparatively low behavioral engagement highlights a notable attitudinal-behavioral gap that merits future research. Overall, competence mapping offers a diagnostic basis for tailored professional development and enables personalized training by identifying specific competence gaps across groups and dimensions, while also guiding the formulation of organizational policies and strategic directions. By aligning resources and interventions with individual and institutional needs, the study advances the emerging field of AI in education and offers a concrete foundation for strengthening educators’ readiness to engage meaningfully with AI in teaching.

Keywords: Artificial Intelligence; Assessment; Competence; Digitalization; Education