Abstract:

Since the rapid rise of Generative Artificial Intelligence (GenAI) in 2023, AI literacy has emerged as a critical competency for teachers. AI literacy is defined as a multidimensional construct that extends beyond technical skills to include four key dimensions: knowing and understanding AI concepts, applying AI tools effectively, evaluating technologies critically, and navigating ethical considerations such as bias and privacy. It is a fundamental prerequisite for responsible AI integration in education, enabling teachers to harness AI for personalized learning and data-driven instruction. Despite its importance, the determinants of teachers' AI literacy, particularly the role of technology acceptance, remain underexplored. This study aims to bridge this gap by examining the relationships between teachers' AI literacy and AI acceptance, using the AI Device Use Acceptance (AIDUA) model.

The study employed a quantitative research design involving 270 teachers in Israel. Participants completed an anonymous online survey comprised of validated scales measuring AI literacy and the six dimensions of the AIDUA model: social influence, hedonic motivation, performance expectancy, effort expectancy, willingness to use AI, and emotions toward AI. Data analysis included descriptive statistics, Pearson correlations, and hierarchical multiple regression to determine the unique contribution of acceptance variables to predicting AI literacy.

The findings reveal that among AI acceptance variables, hedonic motivation and willingness to use AI emerged as the most significant predictors. This suggests that intrinsic motivation and a readiness to engage with AI are more critical for developing literacy than perceived utility alone. Conversely, effort expectancy was negatively associated with AI literacy. A significant interaction effect was found regarding education level: teachers with a master's degree or higher exhibited a stronger negative relationship between effort expectancy and AI literacy compared to those with a bachelor's degree. This indicates that highly educated teachers may perceive AI as more complex or cognitively demanding, which hinders their AI literacy development.

This study contributes to the theoretical understanding of AI literacy as a construct driven primarily by affective and motivational factors. The practical implications suggest that professional development programs should move beyond technical instruction to focus on experiential, "low-stakes" engagement that fosters hedonic motivation and curiosity. Furthermore, training must be differentiated: while novice users benefit from general engagement, teachers with advanced academic backgrounds require targeted support to reduce perceived complexity and effort expectancy. By addressing these psychological barriers, educational leaders can promote a more equitable and effective integration of AI in schools.

Keywords:

Artificial Intelligence (AI), AI Literacy, AI acceptance, hedonic motivation, willingness to use AI.