GenAI Acceptance Modeling in Islamic Higher Education: An Integration of TAM and EVT Using PLS-SEM - Fernanda, Jerhi Wahyu; Donasari, Renita; Anuraga, Gangga; Rahman, Fathur (Southeast Asian Journal of Islamic Education, 2024)
Generative artificial intelligence (GenAI) technology is currently receiving special attention and has numerous benefits. In the education field, this technology can help obtain information quickly to complete a thesis. This research aims to conduct GenAI Modeling based on the Technology Accepted Model (TAM) and Expected Value Theory (EVT) framework using the Partial Least Square Structural Equation Model (PLS-SEM). The research used primary data obtained from surveys. The population was all Tarbiyah faculty students who took a thesis in the Even Semester of the 2023/2024 academic year with a total of 1266. The sample in this research was 191 students who were completing their thesis and had used Gen AI technology to help complete their thesis. The sampling technique used cluster random sampling with a procedure of dividing students into 8 clusters based on the study program. The research instrument used a questionnaire consisting of 5 latent variables: Perceived Usefulness, Perceived Ease of Use, Intrinsic Motivation, Perceived Value, and Behavioral Intention to Use. The results of the analysis using the PLS-SEM method showed that Intrinsic Motivation has a significant relationship with Perceived Ease of Use, and Intrinsic Perceived Usefulness and Perceived Value have a significant relationship with Behavioral Intention to Use. These results show that students choose GenAI Technology to help complete their thesis based on its benefits, such as making it easier to prepare backgrounds, research instruments, and data analysis steps, as well as providing insight into knowledge related to the topic being researched. The research results imply the need for policies regarding the use of GenAI technology for theses so that students are wiser in using GenAI technology.