Mapping scientific production on literacy in generative artificial intelligence: trends, gaps and critical challenges

Abstract

This article examines how generative artificial intelligence is reshaping the field of information literacy and competency, introducing ethical, critical, and epistemological challenges for contemporary academic training. The study adopts an exploratory approach, grounded in documentary research and bibliometric analysis of 133 publications indexed in the Dimensions database. To map the main trends, authors, themes, and gaps in the scientific literature, the VOSviewer software was used to visualize networks of co-occurrence of terms, co-authorship between countries and co-citation between authors and journals. The findings reveal a rapidly growing academic interest in the topic, primarily concentrated in countries of the Global North, as well as in fields such as education, computer science, and library and information science. The literature demonstrates a strong focus on technical and operational competencies in the use of generative artificial intelligence systems. In contrast, critical thinking, cognitive autonomy, ethical responsibility, and epistemic justice remain underexplored. This gap highlights the disconnect between instrumental mastery and the development of critical literacy. Furthermore, it identified the limited participation of countries from the Global South in international collaboration networks and the absence of qualitative studies that investigate, from a situated perspective, how students, faculty, and researchers understand and use these technologies in their academic contexts. The study concludes that it is urgent to rethink the training models adopted in higher education institutions, integrating critical, ethical, and metacognitive competencies, and recommends expanding the descriptors and sources in future research to encompass more plural and contextualized perspectives.