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Student Psychometric Analysis Through Machine Learning

Anagha Shailesh Kulkarni1 , Kumudavalli M.V2 , Vanitha 3

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-09 , Page no. 1-3, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si9.13

Online published on Apr 30, 2019

Copyright © Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha . 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: Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha, “Student Psychometric Analysis Through Machine Learning,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.09, pp.1-3, 2019.

MLA Style Citation: Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha "Student Psychometric Analysis Through Machine Learning." International Journal of Computer Sciences and Engineering 07.09 (2019): 1-3.

APA Style Citation: Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha, (2019). Student Psychometric Analysis Through Machine Learning. International Journal of Computer Sciences and Engineering, 07(09), 1-3.

BibTex Style Citation:
@article{Kulkarni_2019,
author = {Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha},
title = {Student Psychometric Analysis Through Machine Learning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {09},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {1-3},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=942},
doi = {https://doi.org/10.26438/ijcse/v7i9.13}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i9.13}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=942
TI - Student Psychometric Analysis Through Machine Learning
T2 - International Journal of Computer Sciences and Engineering
AU - Anagha Shailesh Kulkarni, Kumudavalli M.V, Vanitha
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 1-3
IS - 09
VL - 07
SN - 2347-2693
ER -

           

Abstract

Psychology can be defined as the mental characteristic or attitude of a person, especially those affecting behavior in a context. Every psychological test has an objective and standardized measurement of a sample behavior. Here, sample of behavior refers to an individual’s response on a situation or task which is prescribed or predefined before the task. In order to make the psychological test cost, time, and efficiency effective, we focus on building a Machine Learning classification model which predicts if the student who took the survey belongs to an Introvert category or an Extrovert category. The questions in the survey will focus on an individual features to build a model and questions prepared by the domain expert will carry particular weight, and depending on the answers we will predict which category the person falls under. The performance of the model is predicted by taking Accuracy and confusion matrix into consideration. It is induced for the betterment or ease of analyzing a personality in order to enhance individual’s strength, enhancing professional and personal skills.

Key-Words / Index Term

psychology, behavior, machinelearning,skills

References

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