Extending TAM With Trust And Transparency To Examine AI Adoption In Higher Education - Cynthia Hayat (ISB Atma Luhur, 2026)
The increasing use of AI in campuses has led to significant changes in the teaching and learning process. However, these changes are followed by several ethical issues related to transparency, trust, and accountability. This study aims to validate the Extended TAM through Trust and Transparency variables that explain the students’ behavioral intentions towards the adoption of AI-driven learning technology. The research design used was an explanatory quantitative design applying an online survey. The sample included 97 undergraduate students in UKRIDA. The collected data were then analyzed using the SEM–PLS method. The results of the model testing showed that cognitive variables (Perceived Usefulness and Perceived Ease of Use) and ethical variables (Trust and Transparency) contribute significantly to forming students’ behavioral intentions, with an R² of 0.66. The finding indicates that the Transparency variable has a positive influence on the Trust and Perceived Usefulness variables, with β values ​​of 0.54 and 0.32, respectively. This study also extends the conventional TAM model by incorporating ethical aspects into the Extended TAM model. The results emphasize the importance of developing transparent and explainable AI systems, strengthening accountability from universities, and increasing AI literacy to support responsible and sustainable AI adoption.