Teacher education for artificial intelligence literacy through a self-determination theory perspective

Existing research often isolates professional development from professional learning communities, overlooking their critical connection. This may hinder the scaling and sustainability of professional learning. This study bridges this gap by applying self-determination theory to investigate how need-supportive professional development impacts teachers’ AI literacy, attitudes, anxiety and engagement in online professional learning communities. Using a sequential mixed-methods approach with 382 secondary school teachers, quantitative results revealed that such professional development enhances AI literacy and fosters sustained behavioural engagement in professional learning communities. Qualitative analysis identified nine specific design strategies for professional development satisfying teachers’ needs for autonomy, competence and relatedness. Theoretically, this validates a motivational pathway from professional development to behavioural engagement in professional learning communities. Within this pathway, AI literacy emerges as the key cognitive driver of sustained participation. Ultimately, the findings underscore that professional development aligned with psychological needs is vital for effective and sustainable AI integration in education.