Bibliometric mapping of data science in education: Trends, benefits, challenges, and future directions - Muhammad Aizri Fadillah; Syafrijon; Sulandari; Febry Azmiana Siregar; Usmeldi (Social Sciences and Humanities Open)
In the digital era, Data Science (DS) plays a crucial role in enhancing education through data-driven decision-making, personalized learning, and curriculum development, yet its broader impact remains underexplored. This study employs bibliometric mapping using VOSviewer software to uncover research trends, thematic clusters, and the global landscape of DS in education. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), a Scopus database-based search identified 551 publications related to DS in education. The results show significant growth in publications since 2014, reflecting increased awareness and investment in DS for improving education quality. The United States leads in contributions, accounting for 45.92 % of the total documents, followed by the United Kingdom (6.53 %) and India (6.35 %). Co-occurrence analysis reveals three main clusters: DS approaches, student interactions with learning, and data analysis techniques. This study identifies key research trends and challenges, including limited infrastructure, skills gaps among educators, and privacy concerns, while addressing gaps in the literature regarding the long-term impact and contextualization of DS in education. The findings indicate DS's impact on curriculum innovation, personalized learning, and data-driven decision-making. These insights not only offer a comprehensive understanding of the current state of DS in education but also provide actionable recommendations for researchers, educators, and policymakers to enhance DS integration and address existing challenges through a multidisciplinary approach.