Trends in Deep Learning Research as an Instructional Approach: A Bibliometric Analysis

Abstrak

This bibliometric analysis aims to uncover and elucidate trends in research with the application of deep learning as a pedagogical tool in education. The study employs bibliometric methodologies using Biblioshiny (RStudio) and VOSviewer software to evaluate publication data obtained from the Scopus database for the years 2015–2024. An examination of 116 research publications indicates an annual growth rate of 17.44%, reflecting a consistent and increasing interest in the academic discipline. A keyword co-occurrence analysis revealed seven prospective research clusters: sustainable higher education and learning methodologies, technology-enhanced learning and digital education, integration of technologies into pedagogical frameworks, learning strategies and assessment techniques, educational psychology, collaborative and active learning, and the incorporation of deep learning in project-based learning methodologies. These findings demonstrate diverse study themes and trends, highlighting the significance of technology integration and new methodologies in education. The findings obtained offer direction for future study, especially in promoting cross-cluster multidisciplinary studies and enhancing international research connections.