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Evaluating the Performance of Teaching Assistant Using Decision Tree ID3 Algorithm

by K. Devasenapathy, S. Duraisamy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 164 - Number 7
Year of Publication: 2017
Authors: K. Devasenapathy, S. Duraisamy
10.5120/ijca2017913658

K. Devasenapathy, S. Duraisamy . Evaluating the Performance of Teaching Assistant Using Decision Tree ID3 Algorithm. International Journal of Computer Applications. 164, 7 ( Apr 2017), 23-27. DOI=10.5120/ijca2017913658

@article{ 10.5120/ijca2017913658,
author = { K. Devasenapathy, S. Duraisamy },
title = { Evaluating the Performance of Teaching Assistant Using Decision Tree ID3 Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 164 },
number = { 7 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume164/number7/27497-2017913658/ },
doi = { 10.5120/ijca2017913658 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:10:41.705551+05:30
%A K. Devasenapathy
%A S. Duraisamy
%T Evaluating the Performance of Teaching Assistant Using Decision Tree ID3 Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 164
%N 7
%P 23-27
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining (DM) is a class of database application that look for the hidden patterns in a collection of data and their relationships. DM is used in developing methods for discovering facts from data which come from educational environment and it becomes educational data mining (EDM). The educational institutions can use classification for complete analysis of students’ characteristics. This paper details the Iterative Dichotomiser (ID3) algorithm in classification technique. The ID3 algorithm builds a decision tree from a dataset. This action we accumulates Teaching Assistant Evaluation’s (TAE) dataset from UCI machine learning repository. This paper demonstrates the ID3 algorithm to construction of decision tree (DT). The implementation of this algorithm is useful to study of teaching performance over three regular semesters and two summer semesters of 151 Teaching Assistant (TA).In this work various kinds of impurities measures and discovery the maximum information gain at various iterations levels. This task is to extract the knowledge that describes TA performance over summer and regular semester. This exertion will help the institute to growth the performance.

References
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  2. Baker, R.S.J.d. (2010) Data Mining for Education. In. McGaw, B., Peterson, P., Baker, E. (Eds.) International. Encyclopedia of Education 3rd edition. Elsevier, Oxford (2010).
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  7. Quinlan, J. R. (1986). "Introduction of decision tree", Machine learn, 1: pp. 86-106.
  8. Devasenapathy.K and Duraisamy “Foreword of Computer Based Techniques in Educational Data Mining and Applying Data Mining Methods in Traditional Educational System”, International Journal Applied Engineering Research ISSN 0973- 4562 Vol.10 No.21 pages 20375–20381.
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  10. U.S. Department of Education, Office of Educational Technology, Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief, Washington, D.C., 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Educational Data Mining Iterative Dichotomiser 3 (ID3) Algorithm Decision Tree Teaching Assistant

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