Mapping the Rise of AI Literacy in Language Education: A Systematic Literature Review and Bibliometric Analysis of Scopus Publications
DOI: https://doi.org/10.65840/jllcd.v2i3.35
Artificial Intelligence, AI Literacy, Language Education, Generative AI, Bibliometric Analysis, Teacher Readiness, AI Ethics
Abstract
Artificial intelligence (AI) has rapidly transformed educational practice, particularly in language learning environments where generative AI tools are increasingly used for writing support, feedback, translation, and personalised instruction. Despite this expansion, knowledge on AI literacy in language education remains fragmented across disciplines and lacks a comprehensive synthesis of its global development. This study therefore investigates publication trends, intellectual structures, emerging themes, and future directions in this field. A systematic literature review integrated with bibliometric analysis was conducted using 198 Scopus-indexed publications retrieved in April 2026. Data were analysed using VOSviewer through publication trend analysis, keyword co-occurrence mapping, overlay visualisation, and density visualisation. The findings reveal a sharp increase in scholarly output after 2024, indicating intensified research attention following the widespread diffusion of generative AI technologies. Thematic mapping identified four dominant clusters: teacher readiness and professional development, AI-assisted language learning, generative AI applications in EFL and ESL contexts, and critical AI literacy related to ethics and learner autonomy. Overlay analysis further demonstrates a shift from early tool-adoption studies toward more recent concerns with engagement, pedagogical integration, and responsible AI use. Density analysis shows that while AI literacy and generative AI dominate the literature, assessment models, multilingual contexts, and longitudinal intervention studies remain underdeveloped. The study concludes that AI literacy has evolved into a multidimensional competence central to the future of language education. These findings provide implications for curriculum design, teacher preparation, and policy development, while offering a research agenda for more inclusive and evidence-based AI integration.
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