Generative artificial intelligence (GenAI) has diffused through higher education faster than the structures meant to govern it, yet acceptance research still treats adoption as a terminal outcome rather than as an event embedded in students' self-regulation. This study extends the Unified Theory of Acceptance and Use o...
An extended acceptance model that incorporates perceived content quality, trust, perceived risk, self-regulated learning, self-regulated learning, and digital–AI literacy is developed and tested and discusses theoretical and practical implications for platform design and institutional policy.
The findings indicate that students' acceptance of PLC learning is most strongly associated with the perceived educational value of PLC instruction, while positive attitudes serve as the most important predictor of continued intention to engage with PLC learning.
The findings indicate that teachers' adoption decisions are jointly driven by instrumental value and institutional provisioning, and that generalized technology anxiety is not, in itself, a barrier among teachers who already have practical exposure to GenAI.
