A Bibliometric Analysis of Digital and Information Literacy Research in Higher Education

Abstract Digital and information literacy have become fundamental competencies for students and academic staff amid digital transformation and generative artificial intelligence. This study maps the growth, collaboration, and knowledge structure of digital-information literacy research in higher education through bibliometric analysis. Data were retrieved from Scopus (exported 16 September 2026), yielding 2,449 initial records. Rule-based inclusion-exclusion screening of titles, abstracts, and keywords produced 1,579 relevant articles published 2015–2026. Analysis was conducted using bibliometrix/biblioshiny in R, covering annual publication and citation trends, country/institution/author distribution and collaboration, source analysis, keyword co-occurrence, trend topics, and thematic mapping. Results show steady growth from 53 articles (2015) to 260 (2025), led by the United States, United Kingdom, and Spain, though author collaboration remains highly fragmented. The thematic map separates a methodologically oriented motor theme (“human,” “humans,” “education”) from a large cluster of core literacy keywords (“digital literacy,” “information literacy,” “higher education”), while trend topics show “artificial intelligence” and “AI literacy” emerging as fast-growing themes since 2023. Compared with prior bibliometric studies that typically stop at 2023–2024 and rely on a single “digital literacy” keyword, this study broadens the literacy construct and extends coverage to mid-2026, applying explicit rule-based screening. Findings offer empirical guidance for researchers, higher-education policymakers, and academic librarians in shaping literacy strategies for the generative-AI era.