EXPLORING ISLAMIC UNIVERSITY STUDENTS’ ACCEPTANCE OF AI INTEGRATION IN ENGLISH SPEAKING PRACTICE: A TAM-BASED STUDY - Yavani, Zakky; Hartono, Rudi; Haryanti, Rahayu Puji; Fitriati, Sri Wuli (The Proceedings of English Language Teaching, Literature, and Translation (ELTLT), 2025)
The integration of artificial intelligence (AI) into language education has created new opportunities for English as a Foreign Language (EFL) learners, especially in speaking practice, where traditional classrooms often provide limited opportunities, delayed feedback, and high-anxiety conditions. Yet, few studies have examined AI acceptance within Muslim-majority higher education contexts where cultural and institutional factors may influence adoption. Guided by the Technology Acceptance Model (TAM), this study investigated English Language Teaching (ELT) students’ perceptions of usefulness (PU), ease of use (PEOU), attitude (ATT), and intention to use (ITU) AI tools for speaking practice at an Islamic university in Indonesia. A quantitative descriptive survey design was employed with 110 third-semester students, using a TAM-based questionnaire, analyzed through descriptive statistics . Findings indicated consistently high PU, particularly in enhancing confidence, fluency, vocabulary, and grammar, as well as high PEOU, reflecting the intuitive nature of AI tools. Attitudes were uniformly favorable, while ITU, though high, was slightly lower and more varied, suggesting that external factors such as affordability, infrastructure, and cultural concerns may limit adoption. The study affirms TAM’s explanatory power while underscoring its limits in fully capturing contextual influences. Its novelty lies in applying TAM within an Islamic higher education setting, contributing theoretical, pedagogical, and policy insights. Limitations include the single-site scope, reliance on self-reported data, and cross-sectional design, indicating the need for multi-institutional, longitudinal, and extended-TAM research.