Survey evaluates readiness for AI in English language teaching among faculty and students, highlighting gaps in preparedness.
Background. Azerbaijani higher education is undergoing rapid digital transformation amid global advances in artificial intelligence (AI). English language teaching (ELT) in Azerbaijan faces the challenge of integrating AI tools to enhance learning, yet little is known about how prepared educators and learners are for this shift. Aim. This study aims to compare ELT faculty and student readiness for AI-integrated teaching and learning at a public Azerbaijani university, identifying gaps and needs to inform capacity-building. Method. A convergent mixed-methods approach was adopted. Quantitatively, a survey measured technological and mindset readiness among 150 bachelor-level ELT students and 16 ELT faculty. Qualitatively, two focus group interviews explored perceptions of AI in education. Results. Survey results (simulated data) indicate that students report higher technology familiarity and more positive attitudes toward AI than faculty. Faculty demonstrate cautious optimism but lower self-assessed AI skills. Focus groups revealed both groups see potential benefits (e.g. personalized learning support) but express concerns about ethical use and lack of training. Conclusion. There is a notable readiness gap: students appear more comfortable adopting AI, while faculty require support to integrate AI pedagogically. Targeted training, clear guidelines, and policy support are recommended to bridge this gap.
No takes yet. Share an insight, caveat, or question.
Zarifa Sadiqzade (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: