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Thanh Ngoc Dan Nguyen
Vi Thi Thuy Ha


Higher education data is growing, but the exploitation and extraction of meaningful knowledge for management have not been paid much attention. The existing mining tools are not effective. This study aims to introduce three techniques for educational data mining: (1) Classification techniques, (2) Predictive models, (3) Clustering techniques. Simultaneously, the study also proposes some solutions to analyze and visualize data, predict students’ learning capacity and assemble  learners. Thereby, education managers could choose appropriate data mining solutions for effective management and training.


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How to Cite
Nguyen, T. and Ha, V. (2019) “AN OVERVIEW OF EDUCATIONAL DATA MINING”, The Scientific Journal of Tra Vinh University, 1(1), pp. 56-60. doi: 10.35382/18594816.1.1.2019.88.


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