AI Adoption Among Europe’s School Evaluators: Awareness and Challenges

This study examines European external school evaluators’ awareness, perceptions, and acceptance of artificial intelligence (AI) in external school evaluation. Drawing on the Technology Acceptance Model (TAM) theoretical framework, this research explores how evaluators’ familiarity with AI, perceived ease of use (PEoU), and perceived usefulness (PU) shape their willingness to integrate AI tools. A mixed-methods approach incorporated a questionnaire (n=56) and semi-structured interviews (n=6), revealing moderate awareness of AI’s capabilities and an overall optimism about potential efficiency gains. However, adoption remains limited, hindered by insufficient training, infrastructural challenges, and ethical concerns regarding data privacy and algorithmic bias. The findings underscore the importance of targeted professional development, robust ethical frameworks, and adequate technological support for successful AI adoption in external school evaluation processes. By addressing these barriers, policymakers and inspectorates can leverage AI’s potential to enhance the accuracy, consistency, and efficacy of external school evaluations.