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A Proposed Framework for Big Data Analytics in Higher Education

Authors :
Nasreen Khan
Beenu Mago
Source :
International Journal of Advanced Computer Science and Applications. 12
Publication Year :
2021
Publisher :
The Science and Information Organization, 2021.

Abstract

Students, faculties, and other members of the higher education (HEd) system are increasingly reliant on various information technologies. Such a reliance results in a plethora of data that can be explored to obtain relevant statistics or insights. Another reason to explore the data is to acquire valuable insight regarding the novel unstructured forms of data that are discovered and often found to have a connection with elements of social media such as pictures, videos, Web pages, audio files, etc. Moreover, the data can bring additional valuable benefits when processed in the context of HEd. When used strategically, Big Data (BD) provides educational institutions with the chance to improve the quality of education from all the perspectives and steer students of HEd toward higher rates of completion. Further, this will improve student persistence and results, all of which are facilitated by technology. With this aim, the current research proposes a framework that analyzes the data collected from heterogeneous sources and analyzes using BD analytics tools to do various types of analysis that will be beneficial for different learners, faculties and other members of HEd system. Moreover, current research also focuses on the challenges of acquiring BD from various sources.

Details

ISSN :
21565570 and 2158107X
Volume :
12
Database :
OpenAIRE
Journal :
International Journal of Advanced Computer Science and Applications
Accession number :
edsair.doi...........3cad0dd2b77b02192746735fafd17d96
Full Text :
https://doi.org/10.14569/ijacsa.2021.0120778