Mapping the Intersection of MOOCs, AI Literacy, and Multilingual Academic Writing: A Bibliometric Analysis of Global Research Trends and Knowledge Structures

Gaukhar Yersultanova, Zhanar Zhyltyrova, Aidos Myrzabek, Zulyar Kavashev, Ainur Aliyeva

2026

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DOI 10.46328/ijtes.8537
Data confidence 70 medium
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Abstract

This study aims to examine scientific publications produced at the intersection of massively open online courses (MOOCs), AI literacy, and multilingual academic writing using bibliometric methods, covering the period from 2020 to 2026. Thirty-eight publications obtained from the Web of Science and Scopus databases and scanned according to the PRISMA protocol form the focus of the bibliometric analysis performed via VOSviewer software and the qualitative content analysis conducted using a mixed inductive-deductive approach. The findings reveal a significant and accelerating upward trend in publication volume during the period examined. This increase, particularly accelerating from 2023 onwards, coincides with the widespread integration of generative AI tools into academic contexts. Geographic distribution shows a dominance of China-based institutions; however, studies from countries such as Rwanda, Kazakhstan, and Indonesia also contribute to discussions on linguistic justice and multicultural representation in the literature. Keyword co-occurrence analysis revealed four core conceptual clusters: AI literacy frameworks and academic writing norms; technology-assisted language learning and student outcomes; ethical concerns and critical gaps; and language MOOCs and cultural context. Content analysis findings were structured around three interconnected thematic frameworks: multilingual academic writing and AI-assisted literacy tools; technological and institutional variables influencing AI adoption; MOOC design and the pedagogical implications of AI literacy in multilingual language education. The study emphasizes the need for MOOC design to be sensitive to the identities of multilingual learners and for the systematic integration of AI literacy components into higher education programs. As one of the first bibliometric studies to address these three areas together, the research provides a unique reference framework for the fields of educational sciences, Applied Linguistics and science of science.