Bibliometric Analysis of the Deep Learning Approach in Teaching the English Language
Abstract
This bibliometric analysis examines the evolving and swiftly growing domain of research on the implementation of deep learning methodologies in English language instruction. The ongoing transformation of the educational landscape by artificial intelligence (AI) has sparked significant interest in incorporating deep learning techniques among researchers and educators seeking to enhance language learning outcomes. This study utilises a selected dataset of 196 peer-reviewed articles published from 2019 to 2023, showcasing the most recent advancements in this interdisciplinary field. This global viewpoint highlights the increasing acknowledgement of deep learning's capacity to customise education, automate evaluation, and enhance communicative proficiency among English language learners. Unlike conventional machine learning techniques, deep learning provides superior skills in natural language processing, speech pattern recognition, and adaptive feedback generation, which are widely utilised in language teaching settings. This review situates itself at the intersection of applied linguistics, computer science, and educational technology, aiming to provide an in-depth understanding of how deep learning is transforming English teaching approaches. The study enhances understanding of the field's evolution by identifying research patterns, prominent authors, significant publication locations, and funding trends. Moreover, it highlights domains that are yet inadequately examined, encouraging further investigation and creativity in the integration of intelligent systems into English language instruction.