Modelling Acceptance of Artificial Intelligence Technology among Pre-service Teachers in Islamic Higher Education - Nur Laili Indasari (At-tadzkir: Islamic Education Journal, 2026)
This study investigates the level of acceptance of artificial intelligence (AI) among pre-service teacher students in Islamic Higher Education Institutions (PTKI) in Gresik Regency, identifies the factors influencing their acceptance, and reveals the challenges they encounter when using AI. A mixed-methods design with a sequential explanatory approach was employed. The research was conducted in five PTKI institutions in Gresik Regency, with a total sample of 152 students. In the first step, quantitative data were collected through a questionnaire based on the Technology Acceptance Model (TAM) and analyzed using Structural Equation Modelling (SEM). In the second phase, qualitative data were collected through in-depth interviews. The results indicate that the level of AI acceptance among pre-service teacher students is relatively high (above 3.41) across all measured constructs. Factors influencing AI acceptance include perceived ease of use, perceived usefulness, AI self-efficacy, social factors, and time efficiency. Furthermore, interview findings reveal that students face several challenges when using AI, such as technical limitations, infrastructural constraints, and issues related to Islamic digital ethics. This study offers crucial, context-specific insights into AI dynamics in PTKI settings, serving as a vital reference for policymakers and educators to design culturally and religiously responsive AI-based educational practices.