Big Data and data science: A critical review of issues for educational research

Abstract

Big Data refers to large and disparate volumes of data generated by people, applications and machines. It is gaining increasing attention from a variety of domains, including education. What are the challenges of engaging with Big Data research in education? This paper identifies a wide range of critical issues that researchers need to consider when working with Big Data in education. The issues identified include diversity in the conception and meaning of Big Data in education, ontological, epistemological disparity, technical challenges, ethics and privacy, digital divide and digital dividend, lack of expertise and academic development opportunities to prepare educational researchers to leverage opportunities afforded by Big Data. The goal of this paper is to raise awareness on these issues and initiate a dialogue. The paper was inspired partly by insights drawn from the literature but mostly informed by experience researching into Big Data in education.As a new research paradigm, Big Data in education stimulates new ways of framing research questions, designing studies, analyzing and visualizing data (Daniel, 2015;Dede et al., 2016). With the availability of large amounts of data in education, researchers can investigate subgroups within a population (a particular group of people), without necessarily relying on sophisticated probabilistic methods (Mayer-Sch€ onberger & Cukier, 2013). Further, Big Data tools enable researchers to collect large amounts of research data with relatively low cost (Mayer-Sch€ onberger, 2015).

Reimaging Research Methodology as Data Science

“…Big Data refers to the description of characteristics of data (volume, velocity, variety, value and veracity), while analytics refers to the various forms of techniques and approaches used to process, manipulate and generate useful insights or outcomes from data (Daniel, 2015;Manyika, et al, 2011) [10,31]. Big Data and analytics are two critical research paradigms that have emerged in an era where society is rapidly generating data in large volumes.…”

“…Big Data and analytics are two critical research paradigms that have emerged in an era where society is rapidly generating data in large volumes. As an emerging paradigm, working with Big Data and analytics requires the knowledge of the 'fourth tradition' [10]. This fourth tradition is an empirical data-intensive scientific approach, which is ingrained in the fundamental principles of knowledge discovery through data mining and visualization, driven by predictive and actionable analytics.…”

“…As a research paradigm, Big Data and analytics requires the use of innovative use of technologies for capturing, storing, distributing, managing and analyzing larger-sized datasets with diverse structures, and visualizing results using dashboards [10]. Big Data stimulates new ways of framing useful research questions and offering researchers with new sets of innovative methodological techniques for capturing, storing, distributing, managing and analyzing larger-sized datasets [10].…”

“…Working with complex data necessitates the development of new methods and analytic tools Gibson and Ifenthaler, 2017;Ifenthaler, 2016;Metzler et al, 2016) [10][11][12][13].…”

“…The evolving nature of various forms of data implies that the current models of the curriculum on research methods are no longer sustainable. Big Data and Data Science, which offer new ways of doing research, also bring new challenges of working with data and design of courses on research methods [10].…”