Preparing for AI-enhanced education: Conceptualizing and empirically examining teachers' AI readiness

Teachers are at the front lines of implementing artificial intelligence (AI) in education. They are expected to develop an adequate understanding of AI and become educated users as well as educators. Their readiness for the use of AI is critical for the success of AI-enhanced education. The present study conceptualized AI readiness from four components: cognition, ability, vision, and ethics in the educational use of AI, and investigated their in-terrelationships and their implications for teachers' work. The data from 3164 primary school teachers were collected and analyzed by partial least square structural equation modelling and cluster analysis. This study found that cognition, ability, and vision in the educational use of AI were positively associated with ethical considerations. The four components of AI readiness all positively predicted, whereas perceived threats from AI negatively predicted, AI-enhanced innovation, which in turn positively predicted teachers' job satisfaction. This study identified three clusters of teachers based on their AI readiness levels. Teachers with high levels of AI readiness tended to perceive low threats from AI and demonstrate high AI-enhanced innovation as well as high job satisfaction. However, teachers from different socio-economic regions and of different genders showed no significant differences regarding AI readiness and its impact on their jobs. This study empirically validated the importance of AI readiness for teachers' work and has important implications for the development of strategies and policies facilitating successful AI-enhanced education.

Automated summary

Teachers play a crucial role in implementing artificial intelligence (AI) in education. This study explores the readiness of teachers in AI use, with four components - cognition, ability, vision, and ethics - and investigates their interrelationships and implications for teachers' work. Findings indicate that cognition, ability, and vision positively influence ethical considerations in AI use. The four components of AI readiness predict AI-enhanced innovation, which in turn predicts teachers' job satisfaction. Cluster analysis reveals different groups of teachers based on their AI readiness levels. This study emphasizes the importance of AI readiness for teachers and provides implications for successful AI-enhanced education.