The Impact of AI Literacy on Undergraduate Autonomous Learning

This study explores the factors driving autonomous learning (AU) among undergraduate students in AI-enhanced education. It specifically examines the role of AI literacy (AI-L), critical thinking (CT), self-regulation (SR), and self-efficacy (SE). Data collected from Thai university students were analyzed using Structural Equation Modeling (SEM). The results show that AI-L demonstrated a strong and significant positive influence on all three mediating variables—SE (β = 0.99, t = 20.00), SR (β = 0.93, t = 18.53), and CT (β = 0.70, t = 7.30). SE exerted as the most powerful predictor of AU (β = 0.52, t = 6.38), while critical thinking had a smaller direct impact. The findings suggest that AI-L is a foundational competency that requires metacognitive support. Consequently, educators should utilize strategies like blended learning and reflective practice. These insights encourage a learner-centered approach to digital education, fostering future-ready, autonomous learners.