Bibliometric Mapping of Big Data (BD) in Higher Education (HE): Towards a comprehensive framework

Abstract

Although big data (BD) has emerged rapidly over the last decade, its importance within higher education (HE) has remained scarce in academic literature. This research aims to develop a comprehensive framework for using big data in HE. We achieved our research objective by conducting a bibliometric analysis of the available literature on BD in HE published in the English language between 2013 -2021. A total of 4312 articles were considered for analysis. Our results showed that most studies focused on the technical specifications of BD, such as data mining and Hadoop. There was a slight reference to the operationality and management functions. However, it is pertinent to note that data privacy, advanced analytics, and machine learning were highlighted as emerging topics. It, therefore, suggests the importance of advanced data analytics and data privacy in establishing a comprehensive framework for managing BD in HE

    Similar works