Relationship between pre-service teachers’ perceived competencies, affective dispositions, and readiness to use artificial intelligence: A study informed by the intelligent-TPACK

As artificial intelligence (AI) continues to reshape educational contexts, understanding pre-service teachers’ (PSTs) readiness to integrate AI into their teaching is increasingly critical. This study explored the relationship among PSTs’ perceived AI competencies, affective dispositions, and intentions to use AI in teaching. Eighty PSTs from a southeastern U.S. university completed an online survey assessing their technological, pedagogical, content, and ethical knowledge related to AI, as well as affective dispositions such as interest, self-efficacy, attitudes, and behavioral intentions. Findings revealed that PSTs reported low-to-moderate AI competencies, with the highest confidence in TPACK and the lowest in technological knowledge and AI ethics. Affective responses were mixed, with moderate interest and perceived relevance of AI, but low self-efficacy and intention to use. Correlational analyses showed strong relationships between AI competencies and positive affective dispositions, particularly self-efficacy and interest, which significantly predicted intention to use AI. Regression analyses further showed that ethical awareness and integrated pedagogical-technological knowledge predicted perceptions of teacher preparation, while ethics also reinforced technological content knowledge. This study highlights the interconnected roles of competency, affect, and ethics in shaping PSTs’ readiness for AI integration in teaching.