Big Data Analytics Applicability in Higher Learning Educational System

Abstract

The application of big data analytics is significantly gaining awareness in the educational sector as universities are operating under pressure in an increasingly competitive environment. Quite a number of researchers have reported the use and application of big data in different fields with few publications addressing the integrative application of big data analytics in institutions of higher education. The purpose of this paper is to explore the applicability of big data analytics in higher institutions. This paper outlines the major areas in which big data analytics can be of use in the higher institutions such as in academic and management levels. The ultimate goal is to optimize using big data analytics in learning and decision-making.

Big Data Analytics Artefact for Outcome-Based Funding Prediction in South African Public Universities

“…This includes improving services that meet the needs of lecturers or learners, as well as obtaining all of the services necessary to efficiently adapt and deploy in the institutions. Tasmin et al (2020) observe that BDA enables organisations to make evidence-based decisions rather than using intuition. The researchers maintain that despite the potential of BDA to improve decision-making within organisations, there are challenges that may hinder organisations from gaining better insights from the received data.…”

“…Though a number of technological options are available to organisations to advance privacy while pursuing data analytics under the privacy by design (PbD) framework, big data security issues are still challenges that need attention during analytics. According to Tasmin et al (2020), various approaches have been suggested to minimize these challenges. These include, but are not limited to, data minimisation that reduces the collection of personal information unless a compelling purpose is outlined, de-identification that is used to remove all information that could identify an individual from a dataset, either directly or through linkages to other datasets, as well as enforcement of user access controls, which grant or deny specific requests to obtain information.…”

A decade of research into the application of big data and analytics in higher education: A systematic review of the literature

“…Early research noted that higher education is a sector yet to be penetrated by Big Data and analytics (Attaran et al, 2018), referring to Big Data as an 'untapped opportunity' in higher education (Chaurasia & Frieda Rosin, 2017). Several early articles discussed the potential of harnessing Big Data in higher education (e.g., Attaran et al, 2018;Daniel, 2017;Tasmin et al, 2020). For example, Daniel (2015) proposed three scenarios in which Big Data can support learning, teaching and administration.…”

Adoption of Big Data Analytics and Its Impact on Organizational Performance in Higher Education Mediated by Knowledge Management

“…BDA is defined as the processing of a large amount of data using mathematical and statistical techniques that allow organizations to discover patterns, identify anomalies, and generate valuable knowledge [15]. BDA is applied in different sectors, including that of education [16]; higher education institutions (HEIs) can collect a large amount of information during the teaching process [16] and use BDA to address the challenges of increasing global competition [15,17]. Under the global context of accelerated change, BDA can provide HEIs with a competitive advantage and a source of open innovation when they manage to gather information from online learning experiences and other sources such as social networks.…”

“…BDA allows them to model individual students' learning behaviors as well as those of the market [18]. In this way, BDA could enable academic and learning analytics to improve the quality of education or optimize the curriculum, or to identify students with a high probability of dropping out of a course before its completion and take personalized counseling actions [19][20][21], among other benefits of data-driven decision making [14][15][16][17]. In addition to BDA, KM processes become paramount when the goal of an organization is to react skillfully and strategically [22], but this requires generating dynamic capabilities.…”