Artificial Intelligence Tools and English Writing Development in Higher Education: A Scopus-Based Bibliometric Analysis Using Biblioshiny and VOSviewer

Abstract

The use of generative AI has transformed the planning, drafting, revising, and assessment of English writing in higher education. Although research on the area has expended rapidly, there is remains a lack of a coherent understanding of the fields intellectual structure, publications patterns, key researchers, collaboration networks, and the thematic development. This study examines the evolution of research on AI tools and English writing in higher education and draws inferences for BS English programmes in Pakistani universities. A Scopus-based dataset was filtered based on year, subject-area, document-type, language, publication-stage, and source-type. From the 2,458 records initially identified, 1,034 English-language journal articles published in the Social Sciences at the final publication stage were included for the period 2020-2026. Performance analysis and science mapping were performed using Biblioshiny/bibliometrix and VOSviewer, respectively. The analysis examined annual scientific production and citations; productive sources and authors; locally cited documents; Bradford’s and Lotka’s laws; h-index indicators; country collaboration; keyword co-occurrence; thematic mapping; trend topics; Reference Publication Year Spectroscopy (RPYS); and a logistic model of the publication life cycle. Scientific production increased from 1 article in 2020 to 431 in 2025 and 354 in 2026; however, the 2026 figure should be interpreted with caution because the year may be unfinished. The conceptual structure was dominated by ChatGPT (257 occurrences), artificial intelligence (223 occurrences), generative AI (114 occurrences), and EFL writing (59 occurrences). Arab World English Journal was the most productive source, while Guo K and Wang Y were the most prolific authors. Bradford’s Law analysis displayed that 18 journals accounted for 34.3% of the literature, while Lotka’s Law showed a highly attentive authorship pattern. Thematic and temporal studies revealed a shift from general research on AI tools and chatbots toward generative AI, large language models, and EFL writing. Overall, the field is rising swiftly but remains uneven across methodological and geographical dimensions. The outcomes highlight the importance of curriculum-integrated AI literacy, process-oriented writing assessment, transparent AI-use disclosure, faculty development, and locally grounded empirical research in Pakistani universities.