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


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 Computer Science 9992: 29th Australasian Joint Conference on Artificial Intelligence (AI 2016): Advances in Artificial Intelligence), 5-8 December 2016, Hobart, Tasmania, pp. 702-707. ISBN 978-3-319-50126-0 (2016) [Refereed Conference Paper]


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Copyright 2016 Springer

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


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:Indigenous Studies
Research Group:Aboriginal and Torres Strait Islander sciences
Research Field:Aboriginal and Torres Strait Islander information and knowledge management systems
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Fan, S (Dr Frances Fan)
UTAS Author:Garg, S (Dr Saurabh Garg)
UTAS Author:Yeom, S (Dr Soonja Yeom)
ID Code:112943
Year Published:2016
Deposited By:Information and Communication Technology
Deposited On:2016-12-05
Last Modified:2018-03-28
Downloads:167 View Download Statistics

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