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Reseach Article

Final Grade Prediction of Secondary School Student using Decision Tree

by Bashir Khan, Malik Sikandar Hayat Khiyal, Muhammad Daud Khattak
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 21
Year of Publication: 2015
Authors: Bashir Khan, Malik Sikandar Hayat Khiyal, Muhammad Daud Khattak
10.5120/20278-2712

Bashir Khan, Malik Sikandar Hayat Khiyal, Muhammad Daud Khattak . Final Grade Prediction of Secondary School Student using Decision Tree. International Journal of Computer Applications. 115, 21 ( April 2015), 32-36. DOI=10.5120/20278-2712

@article{ 10.5120/20278-2712,
author = { Bashir Khan, Malik Sikandar Hayat Khiyal, Muhammad Daud Khattak },
title = { Final Grade Prediction of Secondary School Student using Decision Tree },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 21 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number21/20278-2712/ },
doi = { 10.5120/20278-2712 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:55:31.033113+05:30
%A Bashir Khan
%A Malik Sikandar Hayat Khiyal
%A Muhammad Daud Khattak
%T Final Grade Prediction of Secondary School Student using Decision Tree
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 21
%P 32-36
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Every educational institution around the globe maintain student result repository which contain information about student marks, grade in different subjects and examinations. This repository contains important hidden pattern/knowledge which can be uncovered through data mining. A decision tree classifier based on divide and conquer rules is widely used for data exploration in such repository. In this paper J48 decision tree algorithm is applied on student previous result data to build a model in the form of decision tree. This model can then predict the student final grade. This will be helpful for teacher, student and their parents to know in advance about student final predicted grade and will enable them to take preventive measure.

References
  1. Han, J. , and Kamber. M, (2012) Data Mining: Concepts and Techniques, San Francisco, Morgan Kaufmann.
  2. Alcala, J. , Sanchaz, L. , Garcia, S. , Del Jesus, M. ct. (2007). KEEL :A software tool to assess Evolutionary Algorithms to Data Mining problems. Soft comput, 10. 1007/s00500-008-0323y.
  3. Panday, U. K. , & Pal, S. (2011). Data mining: A prediction of performance or underperformer using classification. International Journal of Computer Science and information technology, 2(2), pp. 686-690.
  4. Ozekes, S. , & Camurcu, A. Y. (2002), classification and prediction in a data mining application, journal of marmara for pure and applied science, 18, pp. 159-174.
  5. Danso, S. O. (2006). An Exploration of Classification prediction techniques in data mining: the insurance domain. [Thesis]. Bournemouth: Bournemouth univeristy.
  6. Quinlan, J. R. (1993), C4. 5: Programs for Machine Learning, San Mateo, CA:Morgan Kaufmann.
  7. Deshpande, S. P. , & Thakare, V. M. (2010), Data mining system and applications: A review, international journal of distributed and parallel system, 1(1), pp. 22-44.
  8. Kabachieva, D. (2013), Predicting Student Performance by Using Data Mining Methods for Classification, Cybernetics and information technologies, 13(1), PP. 61-72
  9. Bhardwaj, B. K. , & Pal, S. (2011), Data mining: A prediction for performance improvement using classification, International journal of computer science and information security, 9 (4), pp. 86-91
  10. Marquez-Vera, C. , Romero, C. , & Ventura, S. (2011). Predicting School Failure Using Data Mining, Proceedings of the 4th International Conference on Educational Data Mining, Eindhoven, The Netherlands, PP. 271-276
  11. Ramaswami, M. , & Bhaskaran, R. (2010), A Chaid based performance prediction model in educational data mining, international journal of computer science issue, 7(1), pp. 10-18
  12. Yadav, S. K. , Pal, S. (2012). Data mining: A prediction for performance improvement of engineering students using classification, World of computer science and information technology journal, 2(2), pp. 51-56.
  13. D'Souza, K. A. , & Maheshwari (2011). Predicting and Monitoring student performance in the introductory management science course, Academy of Educational Leadership Journal, 15, PP. 69-80
  14. Bresfelean, V. P. (2007). Analysis and Predictions on Students' Behavior Using Decision Trees in Weka Environment, Proceeding of the ITI 2007 29th international conference on information technology interfaces, June 25-28, Cavatt, Croutia. pp. 51-56
  15. Ramesh, V. , Parkavi, P. , & Ramar, K. (2013). Predictive student performance: A statistical and data mining approach. International Journal of computer application, 63(8), pp. 35-43.
  16. Prasad, G. N. R. , & Babu, A. V. (2013), Mining previous marks data to predict students performance in their final year examination, international journal of engineering research & technology, 2(2), pp. 1-4.
  17. Frank, E. , and Whitten,I. H. , (2005) Data Mining: Practical Machine learning and technique, San Francisco, Elsevier & Morgan Kaufmann.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Educational Data Mining (EDM) Classification Prediction Decision Tree J48 Data repository Student Grade