Deep Learning in Elementary Education: A Hybrid Systematic Literature Review and Bibliometric Analysis of Global Research Trends (2005-2025)
DOI:
https://doi.org/10.35445/alishlah.v18i3.9882Keywords:
deep learning, elementary education, systematic literature review, bibliometric analysis, educational technologyAbstract
Deep learning has gained increasing attention in elementary education, yet the literature remains conceptually fragmented because the term refers both to artificial intelligence (AI)-based techniques and to pedagogical approaches that promote meaningful, student-centered learning. This study maps the development, conceptualization, dominant themes, and research gaps of deep learning in elementary education. A hybrid Systematic Literature Review (SLR) and bibliometric analysis was conducted using 44 Scopus-indexed journal articles published between 2005 and 2025. The review followed the PRISMA framework, while bibliometric mapping was performed using VOSviewer to examine publication trends, geographical distribution, collaboration patterns, subject areas, and keyword co-occurrence. Publications increased substantially after 2024, with Taiwan, the United States, and China among the leading contributors. Social Sciences represented the largest subject area, followed by Computer Science and Psychology. Keyword analysis identified deep learning, elementary education, students, interactive learning environments, teaching and learning strategies, and project-based learning as prominent themes. The literature reflects an intersection between AI-supported technologies and student-centered pedagogical practices, although international collaboration remains relatively fragmented. The findings indicate a growing convergence between technological and pedagogical perspectives on deep learning in elementary education. Future research should strengthen conceptual distinctions between these perspectives and expand multidisciplinary, longitudinal, ethical, and policy-oriented investigations to support developmentally appropriate and meaningful technology-enhanced learning.
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