Abstract

This study investigates the relationship between Artificial Intelligence (AI) anxiety, AI self-efficacy, and motivated learning among gifted students in Kolej PERMATA Insan, Malaysia. With the increasing integration of AI in education, understanding its psychological impact on high-ability learners has become essential. Grounded in Social Cognitive Theory (SCT), this study explores how psychological factors like anxiety and self-efficacy relate to students' intrinsic motivation in AI-rich learning environments. Adopting a quantitative, correlational research design, data were collected from 150 gifted students using validated survey instruments. The findings revealed that students exhibited moderate levels of AI anxiety and high levels of AI self-efficacy and motivated learning. A significant positive relationship was found between AI self-efficacy and motivated learning, while AI anxiety did not show a significant direct relationship with motivated learning. Furthermore, gender differences were observed, with male students reporting higher AI self-efficacy than females. The study highlights the importance of fostering both emotional and cognitive readiness to enhance learning motivation in AI-integrated educational environments. Practical implications include the need for educators to design psychologically supportive AI-based learning experiences that build self-efficacy and for policymakers to develop training programs that address the affective and cognitive dimensions of AI integration for both students and teachers.