TRAM for AI use in higher education: Pre-service teachers in Indonesia

This study develops and evaluates a Technology Readiness and Acceptance Model (TRAM-based) scale for AI adoption across various Indonesian educational settings. TRAM combines the Technology Readiness Index (TRI)—which measures openness to new tech via optimism (OPT), innovativeness (INN), discomfort (DIS), and insecurity (INS)—and the Technology Acceptance Model (TAM), assessing perceived ease of use (PEOU), perceived usefulness (PU), attitude (AT), and AI-behavioral intention (AI-BI). The samples comprise 1188 Indonesian pre-service teachers. Data were analyzed through measurement and structural models. Based on the model fit and measurement model, the model was found to be valid and reliable, demonstrating the robustness of the data. The findings of the structural model indicate that the most significant relationship is between PU and AT, while the least significant is between DIS and PEOU. Two relationships were insignificant (INN → PU; OPT → PU). The study's findings provided recommendations for education policy, academic development, and teacher training to support SDG 4.