Prediction of Student performance in Higher Education System using R Programming

Authors

  • Neha Kawchale  Department of Computer Engineering, Savitribai Phule University, Pune, Maharashtra, India

Keywords:

Academic analytics, C5.0 algorithm, Logistics regression model, Predictive analytics, R programming language.

Abstract

This document Education plays a vital role in nation’s overall development process. To be effective, analysis related to education sector must be done timely and cope with data scales. Now-a-days the biggest challenges that students face in higher education is predicting the right career paths. Institutions would like to know, which students will be industry ready (get job), who will enroll in which domain and which students will need more assistance in particular subject in terms of job opportunities. Also sometimes, management need more information about student like their result, about the success of new offered courses. Predictive analytics using the R programming language can help and improve the quality of education by analyzing the historical data of the student and allow the decision makers address factors such as unemployment, recommender systems for professional development and curriculum Development to reduce the gap between educational sector and industry requirement. This programming language provides software environment for statistical analysis, graphics representation and finally generates the report. This paper presents an analytical study of student progress report and help to plan accordingly to achieve success using R programming with the help of predictive modelling.

References

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Published

2017-06-30

Issue

Section

Research Articles

How to Cite

[1]
Neha Kawchale, " Prediction of Student performance in Higher Education System using R Programming, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 4, pp.81-87, May-June-2017.