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Understanding the University Student Experience Through Big Data Analytics
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Author(s): Wonkyung Choi (Griffith University, Australia), Jun Jo (Griffith University, Australia)and Geraldine Torrisi-Steele (Griffith University, Australia)
Copyright: 2024
Volume: 15
Issue: 1
Pages: 20
Source title:
International Journal of Adult Education and Technology (IJAET)
Editor(s)-in-Chief: Viktor Wang (California State University, USA)
DOI: 10.4018/IJAET.338318
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Abstract
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of student comments is being undertaken. The first and simplest use of big data analytics is for the identification of high frequency keyword groups, which, without big data analytics, would be extremely time consuming. However, the lack of context surrounding keyword groups severely limited the ability to draw meaningful conclusions and highlighted the need for human intervention in the analysis process. Future work includes sentiment analysis. This initial work is an impetus for further exploration of big data analytics methods in qualitative contexts, especially in dynamic contexts where rapid data analysis can form a basis for timely interventions.
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