NDLI: Predicting School Failure and Dropout by Using Data Mining Techniques

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Predicting School Failure and Dropout by Using Data Mining Techniques

Content Provider	IEEE Xplore Digital Library
Author	Marquez-Vera, C. Morales, C. R. Soto, S. V.
Copyright Year	2013
Abstract	This paper proposes to apply data mining techniques to predict school failure and dropout. We use real data on 670 middle-school students from Zacatecas, México, and employ white-box classification methods, such as induction rules and decision trees. Experiments attempt to improve their accuracy for predicting which students might fail or dropout by first, using all the available attributes; next, selecting the best attributes; and finally, rebalancing data and using cost sensitive classification. The outcomes have been compared and the models with the best results are shown.
Starting Page	7
Ending Page	14
Page Count	8
File Size	272420
File Format	PDF
ISSN	19328540
Volume Number	8
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-02-01
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Classification algorithms Educational institutions Data mining Prediction methods Failure analysis Writing Decision trees Behavioral science Classification school failure dropout educational data mining (EDM) prediction
Content Type	Text
Resource Type	Article
Subject	Education E-learning Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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