Student Grade Prediction by using Machine Learning Methods and Data Analytics Techniques

Anoushka ¹ , Shivani Dubey² , Vikas Singhal³

1. Dept. of Information Technology, Greater Noida Institute of Technology, APJ Abdul Kalam Technical University, Greater Noida, India.
2. Dept. of Information Technology, Greater Noida Institute of Technology, APJ Abdul Kalam Technical University, Greater Noida, India.
3. Dept. of Information Technology, Greater Noida Institute of Technology, APJ Abdul Kalam Technical University, Greater Noida, India.

Section:Research Paper, Product Type: Journal-Paper
Vol.10 , Issue.6 , pp.22-29, Dec-2022

Online published on Dec 31, 2022

Copyright © Anoushka, Shivani Dubey, Vikas Singhal . 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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Abstract :
In the world of an open education system, students have the flexibility to learn anything with ease as the learning content is easily available. This can make the student rather confident as well as careless at the same time. Therefore, it becomes challenging to predict the performance of the student beforehand. In this research, an attempt is made to improve the students’ situations by predicting their performance in advance. This is done by applying the univariate linear regression model. This would help the students improve their performance based on predicted grades and enable teachers to identify those who need assistance. The Main objective of this paper is to implement a simple algorithmic model that predicts the score an individual student that he/she will get at the end of the year. “G3” or the final grade is our label (output) and the rest of the columns will be our features (inputs).

Key-Words / Index Term :
Student Grade System, Data Analytics, Univariate Linear Regression Model

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