Transforming Economics Learning in the AI Era: An Analysis of Senior High School Students’ Acceptance of Artificial Intelligence through the UTAUT Framework
DOI:
https://doi.org/10.33394/jk.v12i1.19636Keywords:
Artificial Intelligence, UTAUT, Economics Education, PLS-SEM, Technology AcceptanceAbstract
This study aims to analyze the factors that influence students’ acceptance of AI use in Economics learning by applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This research employed an explanatory quantitative method with Total sampling, involving 170 students from SMA Negeri 3 Nganjuk, Nganjuk Regency, as respondents. The research instrument consisted of a five-point Likert scale questionnaire measuring six main UTAUT constructs. Data were analyzed using Partial Least Squares – Structural Equation Modeling (PLS-SEM). The findings indicate that Social Influence is the most dominant variable with a significant effect on Behavioral Intention (β = 0.300; p = 0.001), while Performance Expectancy and Effort Expectancy did not show significant effects. Additionally, Facilitating Conditions and Behavioral Intention significantly affect Use Behavior. These results show that the UTAUT model is relevant for explaining AI technology acceptance in Economics learning. The study concludes that Social Influence, Facilitating Conditions, and prior Experience are the dominant determinants of AI acceptance in this context, while Performance Expectancy (β = 0.117; p = 0.204) and Effort Expectancy (β = 0.179; p = 0.053) did not reach statistical significance, findings consistent with Table 6. These results underscore the necessity for educational institutions to prioritize adequate digital infrastructure, foster supportive social environments, and provide progressive exposure to AI technologies to enhance successful implementation in Economics education.
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