Generative AI Use Among Saudi and Korean Language Learners in Higher Education: Examination Through a Modified TAM Framework

This study explores the integration of generative AI (GAI) tools in second language acquisition (SLA) through an extended Technology Acceptance Model (TAM). Focusing on Saudi and Korean English language learners (ELLs), it examines the relationships among perceived ease of use, perceived usefulness, perceived benefits, and actual use (i.e., task-based behavior) of GAI in English foreign language (EFL) learning. While perceived usefulness captures the functional utility of GAI tools for specific language learning tasks, perceived benefits encompass broader educational outcomes, including enhanced language proficiency, greater academic support, and increased learner confidence. Data were collected from 681 participants (407 Saudi, 274 Korean) and analyzed using mean scores, correlation analysis, and structural equation modeling (SEM). The model demonstrated a satisfactory fit, explaining 79% of the variance in actual use, with the model accounting for 70% of the variance in perceived benefits. Comparing models with and without perceived benefits revealed a 6% increase in explained variance ( ΔR 2 = .06). Cross-cultural differences emerged in learner perceptions and adoption intentions, providing a deeper understanding of how students engage with GAI tools in language learning contexts. These findings offer practical insights for the effective integration of AI in SLA settings.