Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers

Abstract

Despite the growing body of research on developing K-12 teachers' generative AI (GenAI) knowledge and skills, its integration into daily teaching practices remains underexplored. Using a snowball sampling method, this study examined the preparedness, practices, and barriers encountered by 89 U.S. teachers in the state of Idaho. Participants were predominantly White, female teachers serving in rural schools. A mixed-methods analysis of survey responses revealed that teachers were generally underprepared for integrating GenAI, with fewer than half incorporating it into their educational practices. Unlike the widespread classroom integration patterns observed with general educational technologies, teachers in this study tended to use GenAI for out-of-classroom duties (i.e., lesson preparation, assessment, and administrative tasks) rather than for real-time teaching and learning. These preferences could be attributed to key barriers teachers faced, including doubts about GenAI's ability to manage risks (i.e., technology value beliefs), reduced human interaction in instruction (i.e., pedagogical beliefs), ethical considerations, and the absence of policies and guidance. This study highlights the need to develop support systems and targeted policies to facilitate teachers' GenAI integration, offering implications for Idaho's education system and the broader U.S. context.