Inquiry of Personal Intelligence Of Adolescence and Early Adulthood College Students of Tamilnadu using Id3 Algorithm
S.Muthukumaran1, P.Geetha2, E.Ramaraj3

1S.Muthukumaran, Research Scholar, Department of Computer Science, Alagappa University, Karaikudi, India.
2P.Geetha, Associate Professor, Department of Computer Science, Dr. Umayal Ramanathan College for Women, Karaikudi, India.
3E.Ramaraj, Professor and Head, Department of Computer Science, Alagappa Univeristy, Karaikudi, India.

Manuscript received on 05 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 1160-1165 | Volume-8 Issue-10, August 2019 | Retrieval Number: J91360881019/2019©BEIESP | DOI: 10.35940/ijitee.J9136.0881019
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Abstract: Educational Data Mining is an Emerging research domain which focus on extracting knowledge from educational databases to promote the learning environment. Educational psychology helps to understand the differences in learning process of a person from cognitive and behavioral perspective. This research aims to predict the personal intelligence of adolescence and early adulthood who are studying under graduate and post graduate courses in educational institution. Adolescence plays a very import role in the development of personality to new dimensions in human life. The Adolescence physical, mental, social, moral and spiritual outlooks undergo revolutionary changes. Many teachers and parents fail to asses these changes and they do not like to slacken their control over them. Psychologist has stressed to properly channelize the behavior of adolescence and give them adequate education. In this paper machine learning technique with decision tree induction algorithm was used to analyze the personal intelligence of college students. To construct the decision tree, Entropy and Information Gain are used as attribute selection measures in ID3 algorithm. Applying data mining techniques in the field of Educational Psychology is a new method and the rules generated from the decision tree helps to identify the personal intelligence of the students. This result helps the Educators to improve the learning environment better for Adolescence.
Keywords: Educational Psychology, Educational Data Mining, Decision Tree Induction Algorithm.
Scope of the Article: Data Mining