The Influence of Artificial Intelligence (AI) Acceptance, Critical Thinking, and AI Dependency on Academic Resilience in Language Learning among Islamic Elementary Teacher Education
Abstract
The rapid development of Artificial Intelligence (AI) has transformed higher education, including language learning among Islamic Elementary Teacher Education (PGMI) students. Its benefits may depend on students’ AI acceptance, critical thinking, and AI dependency, yet few studies have examined these factors simultaneously in relation to academic resilience in PGMI language learning. This study therefore examines the levels of these three variables and their partial and simultaneous effects on academic resilience. A quantitative survey was conducted with 44 PGMI students (semesters 4 and 6), selected through purposive sampling, using a five-point Likert-scale questionnaire and multiple linear regression. AI acceptance was high (M = 4.04), critical thinking very high (M = 4.40), AI dependency moderate (M = 2.99), and academic resilience generally high. Critical thinking had a significant positive effect on academic resilience (B = 0.752, p < .001), whereas AI acceptance (B = −0.018, p = .909) and AI dependency (B = 0.136, p = .185) did not. Together, the three variables significantly predicted academic resilience (F = 13.418, p < .001; R² = .502). Critical thinking thus plays a more important role than AI acceptance or dependency. AI integration in language learning should therefore emphasize critical evaluation, verification, reflection, and independent decision-making rather than merely increasing students’ acceptance or use of AI.
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