Generative AI in English Language Education: A PRISMA-Based Systematic Review and Implications for Technical English in Malaysian Polytechnics
Authors
General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)
General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)
General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)
General Studies Department, Polytechnic Port Dickson, Negeri Sembilan (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.100600547
Subject Category: Education
Volume/Issue: 10/6 | Page No: 7861-7875
Publication Timeline
Submitted: 2026-06-06
Accepted: 2026-06-11
Published: 2026-06-29
Abstract
The rapid advancement of Generative Artificial Intelligence (GenAI) has created new opportunities for enhancing teaching and learning across educational contexts, including English language education. Tools such as ChatGPT, Gemini, Copilot, and NotebookLM have demonstrated considerable potential in supporting writing development, personalised learning, communication practice, and learner engagement. Despite growing interest in GenAI, limited research has specifically examined its implications for Technical English education within Malaysian Technical and Vocational Education and Training (TVET) institutions, particularly Malaysian Polytechnics. This study aims to synthesise current evidence regarding the applications, benefits, and challenges of GenAI in English language education and explore its potential relevance to Technical English instruction in Malaysian Polytechnics. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) framework, a systematic review was conducted using studies published between 2021 and 2026. Relevant literature was retrieved from Scopus, Web of Science, ERIC, ScienceDirect, and Google Scholar. Following screening and eligibility procedures, 15 studies were included in the final synthesis. The findings revealed five major themes: academic and technical writing enhancement; personalised learning and learner autonomy; communication skills and vocational English development; learner engagement and motivation; and ethical, pedagogical, and institutional challenges. The review highlights the potential of GenAI to support Technical English learning while emphasising the importance of responsible implementation, AI literacy, and institutional preparedness. The findings provide useful insights for educators, curriculum developers, and policymakers seeking to integrate GenAI into Technical English education within Malaysian Polytechnics.
Keywords
Generative Artificial Intelligence, Technical English, Malaysian Polytechnic, TVET, English language education, PRISMA, systematic review
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References
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