Exploring The High Potential Factors That Affects Students’ Academic Performance
R. Kaviyarasi1 , T. Balasubramanian2
Section:Research Paper, Product Type: Journal Paper
Volume-6 ,
Issue-8 , Page no. 128-134, Aug-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i8.128134
Online published on Aug 31, 2018
Copyright © R. Kaviyarasi, T. Balasubramanian . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: R. Kaviyarasi, T. Balasubramanian, “Exploring The High Potential Factors That Affects Students’ Academic Performance,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.128-134, 2018.
MLA Style Citation: R. Kaviyarasi, T. Balasubramanian "Exploring The High Potential Factors That Affects Students’ Academic Performance." International Journal of Computer Sciences and Engineering 6.8 (2018): 128-134.
APA Style Citation: R. Kaviyarasi, T. Balasubramanian, (2018). Exploring The High Potential Factors That Affects Students’ Academic Performance. International Journal of Computer Sciences and Engineering, 6(8), 128-134.
BibTex Style Citation:
@article{Kaviyarasi_2018,
author = {R. Kaviyarasi, T. Balasubramanian},
title = {Exploring The High Potential Factors That Affects Students’ Academic Performance},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2018},
volume = {6},
Issue = {8},
month = {8},
year = {2018},
issn = {2347-2693},
pages = {128-134},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2667},
doi = {https://doi.org/10.26438/ijcse/v6i8.128134}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i8.128134}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2667
TI - Exploring The High Potential Factors That Affects Students’ Academic Performance
T2 - International Journal of Computer Sciences and Engineering
AU - R. Kaviyarasi, T. Balasubramanian
PY - 2018
DA - 2018/08/31
PB - IJCSE, Indore, INDIA
SP - 128-134
IS - 8
VL - 6
SN - 2347-2693
ER -
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Abstract
The rapid increase in student population has resulted in expansion of educational facilities at all level. Nowadays, the responsibilities of teachers are many. It is the duty of teachers to guide the students to choose their carrier field according to their abilities and aptitudes. The Data Mining field mines the educational data from large volumes of data to improve the quality of educational processes. Today’s need of educational system is to develop the individual to enhance problem solving and decision making skills in addition to build their social skills. Educational Data Mining is one of the applications of Data Mining to find out the hidden patterns and knowledge in Educational Institutions. Generally, the three important groups of students have been identified: Fast Learners, Average Learners, and Slow Learners. In fact, students are probably struggles in many factors. This work focuses on finding the high potential factors that affects the performance of college students. This finding will improve the students’ academic performance positively.
Key-Words / Index Term
Educational Data Mining; Feature Selection; Ensemble methods; ExtraTree Classifier
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