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Exploring the use of big data analytics for improving support to students in higher education

Citation

Fan, S and Garg, S and Yeom, S, Exploring the use of big data analytics for improving support to students in higher education, Lecture Notes in Artificial Intelligence, 5-8 December 2016, Hobart, Tasmania, pp. 702-707. ISSN 0302-9743 (2016) [Refereed Conference Paper]


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Copyright Statement

Copyright 2016 Springer

Official URL: http://www.springer.com/gp/book/9783319501260

DOI: doi:10.1007/978-3-319-50127-7_63

Abstract

In the past two decades, with the globalisation of education, there has been a continuous increase in the diversity of students in Higher Education. This diversity form a basis for a culturally rich environment, although, the cultural and language differences and the diversity in teaching and learning styles also bring challenges. From a university’s perspective, providing the maximum support to overcome these challenges and achieving maximised student engagement would be in its best interest. Recent advances in Big Data and increase in electronically available education data can help in achieving these aims. This paper reports the findings of a preliminary study which applies Big Data analysis methods to analyse education data gathered from learning management systems. The aims was to understand ways to improve student engagement and reduce student dropout. This paper documents the experience gained in this early exploration and preliminary analysis, and thereby provides background knowledge for reporting of data from the formal data collection stage which will be conducted at a later stage of research.

Item Details

Item Type:Refereed Conference Paper
Keywords:education analytics, big data
Research Division:Information and Computing Sciences
Research Group:Information Systems
Research Field:Aboriginal and Torres Strait Islander Information and Knowledge Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Fan, S (Dr Frances Fan)
Author:Garg, S (Dr Saurabh Garg)
Author:Yeom, S (Ms Soon Ja Yeom)
ID Code:112943
Year Published:2016
Deposited By:Computing and Information Systems
Deposited On:2016-12-05
Last Modified:2017-03-15
Downloads:8 View Download Statistics

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