Digital Literacy in STEM Education: A Bibliometric and Systematic Literature Network Analysis
DOI:
10.29303/jppipa.v12i6.15324Published:
2026-06-25Downloads
Abstract
The rapid development of digital technology and the increasing integration of Artificial Intelligence (AI) in education have transformed learning processes, particularly in STEM (Science, Technology, Engineering, and Mathematics) education. This study aims to analyze the development of research on digital literacy in STEM education through a bibliometric analysis and Systematic Literature Network Analysis (SLNA). The study employed a combination of bibliometric methods, SLNA, and content analysis to identify publication trends, collaboration networks, dominant research themes, and emerging future directions. Data were collected from the Scopus database following the PRISMA 2020 guidelines. A total of 106 relevant articles published between 2019 and 2025 were selected and analyzed using VOSviewer and Orange Data Mining. The findings indicate a significant increase in publications related to digital literacy, AI, and STEM education, particularly in 2025. Bibliometric mapping revealed three major research clusters: technology-integrated teaching and digital literacy in science and engineering education, the role of digital competence and computational thinking in STEM higher education, and the integration of AI and AI literacy in digital literacy development. Topic modeling using Latent Dirichlet Allocation (LDA) identified ten dominant research topics, with technology-based STEM learning and AI-supported education emerging as the most prominent themes. The results also highlight the growing emphasis on AI integration, computational thinking, digital competence, and innovative pedagogical approaches in modern STEM education. Overall, the study demonstrates that research on digital literacy in STEM education is rapidly evolving toward interdisciplinary and AI-driven learning environments. However, challenges remain regarding digital inequality, AI literacy integration, and sustainable pedagogical implementation. This study contributes to the understanding of current research trends and provides future research directions for strengthening digital literacy and AI integration in STEM education.
Keywords:
AI Bibliometric analysis Computational thinking SLNA STEMReferences
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