Student Future Prediction Using Machine Learning

Authors

  • Dileep Chaudhary   Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India
  • Harsh Prajapati   Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India
  • Rajan Rathod   Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India
  • Parth Patel   Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India
  • Rajiv Kumar Gurjwar   Department of Computer Science and Engineering, Parul University, Vadodara, Gujarat, India

DOI:

https://doi.org/10.32628/CSEIT1952300

Keywords:

Career Prediction, Machine Learning, Academic Performance, Linear Regression, Decision Tree Regression

Abstract

Selecting an appropriate career is one of the most important decisions and with the increase in the number of career paths and opportunities, making this decision have become quite difficult for the students. According to the survey conducted by the Council of Scientific and Industrial Research's (CSIR), about 40% of students are confused about their career options. This may lead to wrong career selection and then working in a field which was not meant for them, thus reducing the productivity of human resource. Therefore, it is quite important to take a right decision regarding the career at an appropriate age to prevent the consequences that results due to wrong career selection. This system is a web application that would help students studying in high schools to select a course for their career. The system would recommend the student, a career option based on their personality trait, interest and their capacity to take up the course.

References

  1. UD Beth, HE Janet, Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective. Journal of Interactive Online Learning 2013; 12:17-26.
  2. KS Lokesh, RS Bhakti, et al. Novel Professional career prediction and recommendation method for individual through analytics on personal traits using C4.5 algorithm. IEEE Communication Technology (GCCT) on 3 December 2015.
  3. A Roshani, PR Deshmukh, An incremental ensemble of classifiers as a technique for prediction of student’s career choice. IEEE Networks & Soft Computing (ICNSC) on 25 September 2015.
  4. A Mustafer, Predicting Instructor performance using data mining technique in higher education. IEEE 2016; 4:2379-2387.
  5. C Ling, R Dymitr, et al. Big Data: Opportunities for Big Data Analytics. IEEE Digital Signal Processing (DSP) on 10 September 2015.
  6. M Yannick, X Jie, et al. Predicting Grades. IEEE transactions on signal processing on 15 February 2016
  7. M Jiri, S Jan, AdaBoost. Centre for Machine Perception, Czech Technical University, Prague.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dileep Chaudhary, Harsh Prajapati, Rajan Rathod, Parth Patel, Rajiv Kumar Gurjwar, " Student Future Prediction Using Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.1104-1108, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952300