Artificial Intelligence in English Language Teaching: Bridging Traditional Methods with Modern Technology

Jasiya Rafique; Anu Dhawan; Sara Narjis; Ahlem Saleh Debbabi; Zeinab Aslam

doi:10.63332/joph.v5i12.3763

Authors

Jasiya Rafique Department of English Language Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Anu Dhawan Department of English Language Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Sara Narjis Department of English Language Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Ahlem Saleh Debbabi Department of English Language Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Zeinab Aslam Department of English Language Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

DOI:

https://doi.org/10.63332/joph.v5i12.3763

Keywords:

Artificial Intelligence, English Language Teaching, Traditional Methods, Smart Education, Personalized Learning, Classroom Interaction, Technology in Education, Educational Enhancement, Intelligent Learning Tools, Teacher Facilitation, Pedagogical Shifts, Ethical Data Practices

Abstract

This paper investigates the integration of Artificial Intelligence (AI) in English Language Teaching (ELT), with the aim of bridging traditional teaching methods and modern technological innovations. Over the past decade, conventional ELT approaches — such as the Grammar Translation Method, Direct Method, and Communicative Approach — have laid the foundation for language teaching. However, the emergence of AI tools offers novel opportunities to augment these approaches via personalized, adaptive, data-driven, and feedback-oriented learning environments. Through a comprehensive analysis of recent literature (2021–2025), including systematic reviews, meta-analyses, and empirical studies, this research identifies how AI technologies — such as intelligent tutoring systems, chatbots, speech recognition software, writing assistants, and generative AI tools — are being employed to enhance learners’ skills in reading, writing, listening, and speaking. The review highlights various studies that demonstrate the positive impact of AI in promoting learner engagement, creating individualized learning paths, providing immediate feedback, and fostering autonomous learning. However, the integration of AI in ELT is not without its challenges. These include limited teacher preparedness, ethical and privacy concerns, possible reduction in human interaction, over-reliance on technology, and sociolinguistic limitations (e.g., the tension between standard and global English varieties). This paper, therefore, proposes a balanced theoretical framework for AI-supported ELT. The framework aims to preserve the centrality of the teacher while strategically integrating AI tools into the learning process. Furthermore, it emphasizes the need for ethical data practices, professional training for educators, and a careful consideration of the pedagogical implications of AI in ELT. This hybrid model seeks to harness the strengths of both traditional pedagogy and modern AI technologies to optimize language learning.