Stream Processing for Performance Analysis of Identifying Dropout Students utilizing Different Decision Tree Based Methods

Authors

  • Sumita Guddin  PG Student, Department of CSE/SDMCET/Dharwad, Karnataka, India
  • Dr. R. N. Yadawad  Professor Department of CSE/SDMCET/Dharwad, Karnataka, India
  • Dr. U.P. Kulkarni  Professor Department of CSE/SDMCET/Dharwad, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT228417

Keywords:

Important attributes, Decision tree, various decision tree-based approaches, dropouts.

Abstract

A person's ability to lead a stable, affluent life is made possible through education. In the same way, a country's development may be influenced by the proportion of its population with a higher level of education. This number does, however, decline because of early schooling dropouts. Furthermore, a nation's resources are diminished if a student cannot continue because of a dropout. Although the number of dropouts is constantly falling, it is still very challenging for educational institutions to identify these individuals. An educational institution's first priority is to improve student Performance; therefore, it makes sure that every student graduates on time. Nevertheless, a significant barrier that has a negative effect on this goal is student dropout. Understanding the causes of dropouts is necessary to finding a solution. The causes differ from one student to another; some are connected to the student's workload and mental fortitude. Various ways using Decision Tree (DT) methodologies have been suggested and studied in this study.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-08-30

Issue

Volume 8, Issue 4, July-August-2022

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sumita Guddin, Dr. R. N. Yadawad, Dr. U.P. Kulkarni, " Stream Processing for Performance Analysis of Identifying Dropout Students utilizing Different Decision Tree Based Methods" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 4, pp.150-156, July-August-2022. Available at doi : https://doi.org/10.32628/CSEIT228417