International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 14, No. 2, 8 Apr. 2022
Cover page and Table of Contents: PDF (size: 327KB)
Psychometric Analysis Using Computational Intelligence for Smart Choices
Full Text (PDF, 327KB), PP.65-75
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Author(s)
Index Terms
Psychology, K-NN, SVM, Decision Trees, Machine Learning, Classification
Abstract
Currently with world's industries providing endless job varieties, it is getting difficult for the students to choose optimum career lines. Ranging from 16-24 years old, these age groups find themselves unable to recognize their future endeavors. Hence, psychometric tests provide a solution, helping them to recognize their interests, aptitude and personality traits to produce better results. The research process was facilitated by questionnaires involving verbal, spatial, logical, critical and numerical aptitude. The responses were analyzed using statistical techniques, and machine learning algorithms. A number of graphs were plotted for better understanding of the technical details. The proposed psychometric and aptitude analysis model entails accuracy calculation assigning K-means, KNN, confusion matrices and SVM plots. The results of the psychometric analysis gave broad spectra of career choices by studying the pattern of the choices selected by the people. Respondents were supposed to give information about their interests and perceptions in their day to day activities, which in turn reflect information about their inner humanly traits, unknowingly providing an ideal career path.
Cite This Paper
Vidushi Singla, Rashi Thareja, Reema Thareja, " Psychometric Analysis Using Computational Intelligence for Smart Choices", International Journal of Modern Education and Computer Science(IJMECS), Vol.14, No.2, pp. 65-75, 2022.DOI: 10.5815/ijmecs.2022.02.06
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