Education big data and learning analytics: a bibliometric analysis

Shaza Arissa Samsul (), Noraffandy Yahaya and Hassan Abuhassna
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Shaza Arissa Samsul: Universiti Teknologi Malaysia
Noraffandy Yahaya: Universiti Teknologi Malaysia
Hassan Abuhassna: Universiti Teknologi Malaysia

Palgrave Communications, 2023, vol. 10, issue 1, 1-11

Abstract: Abstract The contemporary era’s extensive use of data, particularly in education, has provided new insights and benefits. This data is called ‘education big data’, and the process of learning through such data is called ‘learning analytics’. Education in big data and learning analytics are two important processes that produce impactful results and understanding. it is crucial to take advantage of these processes to enhance the current education system. We conduct a bibliometric analysis based on the PRISMA statement template. The publications used for the analysis are based on the years 2012–2021. We examine and analyze a total of 250 publications, mainly sourced from the Scopus database, for insights regarding education big data and learning analytics. All of the publications also undergo filtration according to specific inclusion and exclusion criteria. Based on the bibliometric analysis conducted, we discover the distribution of education big data and learning analytics publications across the years 2012–2021, the most relevant journals and authors, the most significant countries, the primary research keywords, and the most important subject area involved. This study presents the trends and recommendations in education big data and learning analytics. We also offer suggestions for improvement and highlight the potential for enhancement of the education system through the full utilization of education big data and learning analytics.

Date: 2023
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DOI: 10.1057/s41599-023-02176-x

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