Visualizing the Educational Data Mining Literature

Visualizing the Educational Data Mining Literature

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Submitted Dec 19, 2020
Published Dec 19, 2020
DOI https://doi.org/10.24018/ejers.2020.0.CIE.2306
Abstract viewed = 47 times
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SPECIAL ISSUE : CIE 2020
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Articles

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  •   I. Papadogiannis

  •   N. Platis

  •   V. Poulopoulos

  •   C. Vassilakis

  •   G. Lepouras

  •   M. Wallace

  •   G. Karountzou

Abstract

This article provides a visualization of a literature review in students’ performance prediction using educational data mining (EDM) techniques for the period 2015-2019. The results of the review are presented concisely and simply with the use of diagrams. Various aspects of the literature are examined, such as the algorithms adopted, the type of results drawn, the educational setting of the application and the actual exploitation of the outcomes. Findings indicate that tertiary education dominates the EDM field; in contrast, the focus given to secondary and primary education is minimal.


Keywords: Visualization, Educational Data Mining, Student Performance, Literature review

References

I. Papadogiannis, M. Wallace, and V. Poulopoulos, “A critical review of data mining for education: what has been done, what has been learnt and what remains to be seen,” International Journal of Educational Research Review, vol. 5, no. 4, pp. 353-372, October 2020.

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How to Cite
[1]
Papadogiannis, I., Platis, N., Poulopoulos, V., Vassilakis, C., Lepouras, G., Wallace, M. and Karountzou, G. 2020. Visualizing the Educational Data Mining Literature. European Journal of Engineering and Technology Research. CIE (Dec. 2020). DOI:https://doi.org/10.24018/ejers.2020.0.CIE.2306.
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