Publication details

Analysis of Student Retention and Drop-out using Visual Analytics



Year of publication 2014
Type Article in Proceedings
Conference Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014)
MU Faculty or unit

Faculty of Informatics

Field Informatics
Keywords student retention; student drop-out; visual analytics; motion charts; animation
Description 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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