Artificial Intelligence for Digital Literacy in Higher Education: A Systematic Literature Network Analysis and Bibliometric Analysis

Rayendra, Fikri Aulia, Dadi Mulyadi, Affero Ismail, Septryan Anugrah, Jodi Hardika

Abstract

This study aims to map the intellectual structure, research trends, and future directions of Artificial Intelligence (AI) for Digital Literacy in Higher Education using a Systematic Literature Network Analysis (SLNA) approach. Data were collected from the Scopus database following the PRISMA 2020 protocol, resulting in 242 journal articles published between 2019 and 2025. Bibliometric mapping was conducted using VOSviewer, while Latent Dirichlet Allocation (LDA) topic modelling was applied to identify thematic patterns and emerging research themes. The findings reveal a substantial increase in publications after 2023, coinciding with the rapid growth of generative AI technologies. Six major thematic clusters were identified, covering AI-based digital literacy, academic integrity and ethics, human-centered factors, pedagogical adoption, digital competence, and AI-supported learning technologies. Topic modelling further revealed ten dominant research themes, with generative AI emerging as the most influential topic in recent years. The study highlights a shift from technology-oriented perspectives toward more pedagogical, ethical, and human-centered approaches. By integrating SLNA, bibliometric network analysis, and LDA topic modelling, this research provides a comprehensive overview of the evolving research landscape and offers strategic directions for future research and policy development in higher education.

 

Keywords: Artificial intelligence; digital literacy; higher education; bibliometric analysis; systematic literature network analysis; topic modelling.

 

DOI https://doi.org/10.55463/issn.1674-2974.53.6.9


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