AI-Supported EFL Learning in Engineering Education and Emerging Pedagogical Practices

The rapid growth of AI technologies offers new chances to improve EFL instruction, especially in engineering education. This systematic review looked at how AI-assisted EFL instruction affected engineering students' language skills and professional skills. It also examined challenges related to ethics, technology, and sustainability while identifying gaps in engineering EFL education in Saudi Arabia. Following PRISMA guidelines, a detailed search strategy was utilised to find empirical studies on artificial intelligence in English language learning by searching reputable databases like IEEE Xplore, SpringerLink, Taylor & Francis Online, ERIC, ScienceDirect, and Wiley Online Library. The results indicated that AI tools improved language ability, student motivation, and communication skills, tailored to specific fields through personalized learning. However, it also found challenges related to ethical, technical, and teaching issues, along with research gaps in AI-assisted English learning for engineering students in Saudi Arabia. The study recommends several teaching implications for EFL instructors and policymakers about integrating AI tools in EFL classrooms to enhance the language skills of engineering graduates

Empirical research · Engineering education · English language · Language acquisition · Sustainability · Systematic review · Artificial Intelligence in Healthcare and Education · Online Learning and Analytics · Technology-Enhanced Education Studies