2019Unpublished venueRequires access

Identification of Drop Out Students Using Educational Data Mining

Nafisa Tasnim, Mahit Kumar Paul, A.H.M. Sarowar Sattar

Open publisher page 23 citations

Abstract

Education makes a human being steady, stable and prosperous in his way of leading life. In the same way, the number of higher educated persons in a country can contribute to the development of the country. However, this number decreases due to dropout of students at early stage of the education. Furthermore, if a student can't continue or drop out, the resources of a nation is attenuated. Although nowadays the rate of drop out students is diminishing, till now it is a huge challenge for an educational institution to identify the dropout students at the beginning. To address this issue, several approaches have been discussed in educational data mining to identify the rate of drop out students. Following this line in this paper, a threshold based approach has been proposed to identify dropout students that outperforms than the existing approaches.

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What this paper is about

Education makes a human being steady, stable and prosperous in his way of leading life. In the same way, the number of higher educated persons in a country can contribute to the development of the country. However, this number decreases due to dropout of students at early stage of the education. Furthermore, if a student can't continue or drop out, the resources of a nation is attenuated. Although nowadays the rate of drop out students is diminishing, till now it is a huge challenge for an educational institution to identify the dropout students at the beginning. To address this issue, several approaches have been discussed in educational data mining to identify the rate of drop out students. Following this line in this paper, a threshold based approach has been proposed to identify dropout students that outperforms than the existing approaches.

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OpenAlex reports 23 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Education makes a human being steady, stable and prosperous in his way of leading life. In the same way, the number of higher educated persons in a country can contribute to the development of the country. However, this number decreases due to dropout of students at early stage of the education. Furthermore, if a student can't continue or drop out, the resources of a nation is attenuated. Although nowadays the rate of drop out students is diminishing, till now it is a huge challenge for an educational institution to identify the dropout students at the beginning. To address this issue, several approaches have been discussed in educational data mining to identify the rate of drop out students. Following this line in this paper, a threshold based approach has been proposed to identify dropout students that outperforms than the existing approaches.

Key concepts: Drop out, Dropout (neural networks), Drop (telecommunication), Educational data mining, Identification (biology), Computer science, Mathematics education, Data science

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