Empowering teachers to use AI for differentiation: changes in teachers’ acceptance of AI-based technologies following participation in a short professional development training session

In increasingly diverse classrooms, artificial intelligence (AI)-based technologies, including large language models (LLMs), are widely discussed as tools to support teachers in implementing differentiation. However, the successful integration of such technologies largely depends on teachers’ social acceptance of these systems. The present study reports findings from a pilot pre-post evaluation of INSIGHT ( Information on Schooling with Generative and Helpful AI Tools ), a short teacher professional development (TPD) training session on AI-based technologies in schools, with a particular focus on LLMs. Pre- to post changes in teachers’ social acceptance of AI-based technologies for supporting differentiation were examined. Drawing on the Technology Acceptance Model (TAM), social acceptance was conceptualised as Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Behavioural Intention (BI). Data were collected from N = 100 teachers from primary and secondary education in Germany. Results of paired-samples t -tests indicated significant pre-post increases in PU and PEOU, whereas no significant change was found for BI. While teachers perceived AI-based technologies as more useful and easier to use after the training, these changes did not translate into a stronger behavioural intention to use these technologies in practice. The discussion therefore considers potential barriers that may influence teachers’ intentions to use AI-based technologies for differentiation.