Factors associated with Chinese vocational college students’ intention to use generative artificial intelligence for learning: an extended UTAUT mode

Research from 'Frontiers in Education (International)' explored the factors influencing Chinese vocational college students' intention to use generative artificial intelligence (GenAI) for learning. The study utilized an extended Unified Theory of behavioral Intention and Use of Technology (UTAUT) model, which incorporated anxiety (ANX), and employed a two-stage analytical approach combining structural equation modeling (SEM) and ordered Probit (OProbit) regression to analyze these factors and their impact on behavioral intention.

Understanding the drivers and barriers, such as anxiety, to technology adoption among vocational students provides critical insights for digital transformation strategies in educational and workforce development. This research highlights the need for targeted interventions to foster effective GenAI integration in learning environments, which can impact future workforce readiness and national competitiveness.

The study focused on Chinese vocational college students' intention to use GenAI for learning.

Forward consideration, not a verified fact.