Student Psychometric Analysis Through Machine Learning

Authors

  • Kulkarni AS Dept. of Computer Applications, Dayananda Sagar College of Arts, Science & Commerce
  • Kumudavalli MV Dept. of Computer Applications, Dayananda Sagar College of Arts, Science & Commerce
  • Vanitha V Computer Science Department, Seshadripuram PU College, Yelahanka

Keywords:

psychology, behavior, machinelearning, skills

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.

References

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Published

2025-11-25

How to Cite

[1]
A. S. Kulkarni, M. Kumudavalli, and V. Vanitha, “Student Psychometric Analysis Through Machine Learning”, Int. J. Comp. Sci. Eng., vol. 7, no. 9, pp. 1–3, Nov. 2025.

Issue

Vol. 7 No. 9 (2019): IJCSE Special Issue April Edition

Section

Research Article

License

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