Predicting Students Performance Using Decision Trees: Case of an Algerian University

被引：0

作者：

Chiheb, Fatma ^{[1
]}

Boumahdi, Fatima ^{[1
]}

Bouarfa, Hafida ^{[1
]}

Boukraa, Doulkifli ^{[2
]}

机构：

[1] Saad Dahlab Univ, Sci Fac, LRDSI Lab, BP 270,Soumaa Rd, Blida, Algeria

[2] Univ Jijel, BP 98, Ouled Aissa 18000, Jijel, Algeria

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON MATHEMATICS AND INFORMATION TECHNOLOGY (ICMIT) | 2017年

关键词：

Data mining; Educational Data Mining (EDM); classification; prediction; decision tree; J48; Algorithm; CRISP-DM methodology;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The data produced from educational activities could be exploited in order to extract useful knowledge, assist educational decision makers in making better decisions and help students achieve better results. In this study, we report our findings about the application of a data mining technique following the CRISP-DM model at the department of Computer Science at the University of Jijel, Algeria. Our proposed system is able to classify undergraduate and post-graduate students according to their results and to predict their performance for the coming years based on their current results and on history data. The system can also be used as an early-warning tool for students at risk and to help graduates in choosing the appropriate Master's disciplines to pursue their studies.

引用

页码：113 / 121

页数：9

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