GÉRYK, Jan and Lubomír POPELÍNSKÝ. Analysis of Student Retention and Drop-out using Visual Analytics. In John Stamper, Zachary Pardos, Manolis Mavrikis, and Bruce M. McLaren (Eds.). Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014). London, United Kingdom: International Educational Data Mining Society, 2014. p. 331-332, 2 pp. ISBN 978-0-9839525-4-1.
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Basic information
Original name Analysis of Student Retention and Drop-out using Visual Analytics
Authors GÉRYK, Jan (203 Czech Republic, belonging to the institution) and Lubomír POPELÍNSKÝ (203 Czech Republic, guarantor, belonging to the institution).
Edition London, United Kingdom, Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), p. 331-332, 2 pp. 2014.
Publisher International Educational Data Mining Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
RIV identification code RIV/00216224:14330/14:00076278
Organization unit Faculty of Informatics
ISBN 978-0-9839525-4-1
Keywords in English student retention; student drop-out; visual analytics; motion charts; animation
Tags International impact, Reviewed
Changed by Changed by: RNDr. Jan Géryk, Ph.D., učo 72902. Changed: 16/9/2014 20:53.
In the paper, we have described the motivation and design of the VA tool EDAIME which is intended for exploratory analysis of educational data. We enhanced the concept of Motion Charts and successfully expanded it to be more suitable for such analyses. We have successfully employed it to verify the suggested hypothesis. A further in-depth analysis with different mapping of variables is needed to quantify the correlations more accurately. Despite the fact that common data visualization methods are quite beneficial, there are types of questions that cannot be examined using them. Since the questions involve quantitative relationship other than change through time.
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