Trends of Deep Learning Approaches in Elementary School: VosViewer-Assisted Bibliometric Analysis - Riza Ahmad Ghozali; Elih Sudiapermana; Sofyan Iskandar Sofyan (Sakura Digital Nusantara, 2026)
Objective: This study aims to analyze the trends, developments, and characteristics of global scientific publications regarding the deep learning approach in elementary schools over an eleven-year period (2015–2025) in order to overcome the limitations of systematic scientific mapping using computational bibliometric approaches in this field. Methods: This study used a quantitative bibliometric design, collecting metadata from 985 deep learning articles in elementary schools indexed through Harzing's Publish or Perish application. Statistical data processing was carried out using Microsoft Excel, followed by computational mapping and analysis of network visualization, density, and overlays using the VOSviewer application to test the relationship between keyword co-occurrence. Findings: The analysis revealed that there are 985 publications with fluctuating trends that tend to increase, peaking at 149 articles in 2025 with an average annual growth of 89.5 publications. The VOSviewer mapping identifies 5 interconnected keyword clusters where the terms