Research Trends, Collaboration, and Impact of Deep Learning in Mathematics Education: A Bibliometric Perspective

Abdur Rahman Hakim* -  Universitas Islam Negeri Sultan Syarif Kasim Riau, Indonesia
Firza Mufti Aulia -  Universitas Islam Negeri Sultan Syarif Kasim Riau, Indonesia

Abstract


This study aims to examine the trends, patterns, developments, and research impact of deep learning in mathematics education. The study employs a quantitative approach using bibliometric analysis to explore the development of this field systematically. Data were obtained from the Scopus database and analyzed using Biblioshiny (Bibliometrix-R), which was used to identify publication trends, citation counts, collaboration patterns among authors and countries, as well as the development of research concepts and themes through various visualizations. The results indicate a rapid increase in the number of publications in recent years, reflecting a growing interest in this topic. In terms of collaboration, researchers still tend to work in small groups, although international collaborations are beginning to emerge. From a thematic perspective, there is a shift from a theoretical focus toward meaningful learning that is relevant to students’ real-life contexts. In addition, the integration of technology in learning is becoming more prominent without neglecting conceptual understanding. In terms of impact, this field demonstrates strong influence, as shown by both foundational studies that continue to be widely cited and recent publications that quickly gain attention. Overall, this study shows that deep learning in mathematics education is continuously evolving toward the integration of technology, conceptual understanding, and meaningful learning experiences.

Keywords


Deep Learning; Mathematics Education; Meaningful Learning; Bibliometric Analysis; Research Trends.

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References


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DOI: https://doi.org/10.24952/ejpm.v3i1.19774

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