Artificial Intelligence and Autonomous EFL Learning: A Mixed-Methods Study of Libyan University Students

Abstract

This study investigates Libyan university EFL students’ attitudes toward AI as a support for autonomous English learning and identifies the main challenges affecting its effective and responsible use. A mixed-methods approach was adopted, combining quantitative and qualitative data from 100 undergraduate EFL students at Sabratha University and semi-structured interviews with 10 students. Quantitative data were analysed using descriptive statistics and Cronbach’s alpha, while interview data were analysed thematically...

Findings revealed widespread and generally positive use of AI, particularly conversational tools such as ChatGPT. Students perceived AI as useful for exploring topics, managing learning, and correcting errors. However, they viewed autonomy as supported independence rather than independence from teachers, recognizing AI as a learning scaffold rather than a replacement for teacher guidance. The most significant challenge was the lack of clear university guidance and training on AI use, alongside concerns about accuracy, privacy, and internet connectivity. Qualitative findings highlighted critical verification, the tension between productivity and dependency, and ethical and affective concerns.

The study concludes that AI-assisted autonomy in the Libyan EFL context requires learner agency, teacher guidance, institutional AI literacy, clear ethical policies, reliable infrastructure, and critical evaluation of AI-generated content.