Claude AI Adoption in High School Learning: An Extended UTAUT Model of Students’ Behavioral Intention and Use Behavior

Abstract

The integration of generative artificial intelligence (AI) into secondary education is creating new opportunities for advanced, adaptive, and student-centered learning, while its educational value depends partly on students' acceptance and actual use of the technology. Therefore, this study examines the acceptance and use of Claude AI in high school economics learning through the UTAUT model, with particular attention to its implications for AI-supported learning innovation and the design of more responsive learning environments. A quantitative survey was carried out among 139 high school students from SMAN 18 Surabaya, and the proposed research model was evaluated by applying PLS-SEM. The measurement model proved the construct validity and reliability in all constructs. The structural model showed that both Performance Expectancy and Social Influence affected Behavioral Intention, whereas Effort Expectancy did not show any statistically significant effect on it. Facilitating Conditions and Behavioral Intention had a significant impact on Use Behavior. The model accounted for 59.3% of the variance of Behavioral Intention and 41.4% of the variance of Use Behavior. Moreover, no moderating effect of age, gender, and experience with Claude AI was observed on the examined relationships in the model. The findings indicate that students' acceptance of Claude AI is primarily associated with perceived learning benefits and social influence, whereas actual use is associated with behavioral intention and facilitating conditions. These findings highlight the importance of integrating generative AI through pedagogically meaningful, student-centered, and context-sensitive learning strategies rather than treating it solely as a technological tool.