AI Mindset – An empirically tested theoretical framework on the psychological factors shaping AI competence and AI use

Artificial Intelligence (AI) has emerged as a powerful tool in the educational sector. Research examining the facilitating factors of its practical application by teachers has increased substantially. Although empirical studies highlight the importance of psychological factors in shaping engagement with AI technologies, the systematic integration of cognitive, emotional, and motivational variables into AI use research remains fragmented. To advance the psychological foundation, the present study proposed and empirically tested AI Mindset model, conceptualised based on prior psychological and social-cognitive theories. The AI Mindset framework posits a triadic structure, comprising dispositional factors, contextual and social facilitation, and technology-related appraisals, to explain teachers’ AI use. Structural equation modelling of 224 teachers revealed that AI Mindset variables are associated with pedagogical AI competence and AI use. Specifically, dispositional factors of openness and need for relatedness associated with AI use indirectly through pedagogical AI competence. Contextual and social facilitations of habit demonstrated the strongest direct associations with AI use and indirect association via competence. In terms of technology-related appraisals, fear showed a complex pattern, with a positive direct link with AI use but a negative indirect link through pedagogical AI competence. The effect of effort expectancy was fully mediated by competence, whereas hedonic motivation showed a direct positive association with AI use. In sum, the present study advances a psychological perspective on AI use in teaching and learning. The framework provides a foundation for understanding AI-related engagement patterns and can inform systematic, intentional improvements in professional development, instructional practice, and AI-supported educational technology design.