Abstract
Background: The interest in big data in education related to the continuous industrial revolutions affecting education and several industries has led to increased publications about it.
Objective: This study aims to identify prevalent big data in education research and describe the temporal trends of topics using data mining.
Methodology: Social sciences-related abstracts were systematically mined from Web of Science and Scopus using the keywords "big data" AND "education". Pre-processing, word frequency and co-occurrence analysis, topic modeling, and trend analysis were done to detect semantic patterns and explore the yearly development of research topics. R packages like udpipe, stopwords, topicmodel were utilized for all data mining processes.
Results: A total of 2290 research articles and reviews related to big data in education were found. Topics with most publications were related to “Data Privacy and Security”, “Educational Networking”, and “Altmetrics”. While topics with the least publications were "Law and Policies", "Business Intelligence", and "Architecture". Overall, except for five, all topics showed an increasingly significant trend (p<0.05) from 2010 to 2022.
Conclusion: The study revealed that there is a large amount of research with varying topic focus since the 2010s. Analyses revealed that although much has been published about this area, truly integrating big data in the process of education has still a long way to go due to limited specific frameworks, guidelines and policies. Results will be beneficial for policy-makers, administrators, educators and other stakeholders in development of guides and training for further integration of big data in education worldwide.
Author Information
Catherine Joy Escuadra, Ewha Womans University, South Korea
Krizia Magallanes, Ewha Womans University, South Korea
Sunbok Lee, Ewha Womans University, South Korea
Jae Young Chung, Ewha Womans University, South Korea
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