AI Self-Efficacy and Human–AI Collaboration Quality as Drivers of Student Creativity: An Extended TAM Model in Jordanian Higher Education

The rapid integration of artificial intelligence (AI) into the higher education sector is essentially reshaping the learning, creative, and knowledge-interaction practices of students. However, there is little empirical research on the degree to which AI-related competencies and human-AI interaction mechanisms can affect student creativity, particularly in the context of developing countries. The current research adds to the Technology Acceptance Model (TAM) by introducing AI self-efficacy as a psychological antecedent and human-AI collaboration quality as an interactional mechanism, which explains creativity among university student groups in Jordan. The information was received through an online questionnaire that was distributed among 366 students studying at four universities in Jordan, including two state-owned and two privately owned institutions, and who had previous experience with AI-based learning tools. Using confirmatory factor analysis and structural equation modelling in AMOS, the research confirms the measurement model and evaluates the hypothesized structural relationships. The results show that AI self-efficacy is a significant supplement to the perception of ease of use and usefulness, which in foster develop more positive attitudes towards AI. The ease of use and usefulness perceptions also have a strong impact on the quality of human-AI collaboration, which strengthens the attitudes of students even more. The attitude towards AI is a powerful predictor of the behavioural intention to use AI, and behavioural intention seems to be a crucial factor in influencing student creativity. The model explains a significant percentage of variance in behavioural intention (R ²  = 0.61) and in creativity (R ²  = 0.47). The findings contribute to the TAM-based AI studies by highlighting the importance of self-efficacy and the quality of collaboration and offer practical implications to universities that wish to use AI as a driver of creative and innovation-driven learning in Jordanian higher education.