Prediction of Student Performance Using Linear Regression

B. Sravani, M. M. Bala
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引用次数: 18

Abstract

This paper is about how the application of machine Learning have huge impact in teaching and learning for further improvement in learning environment in higher education. Due to the interest of students in online and digital courses increased rapidly websites such as Course Era, Udemy etc became very influential. We implement the new applications of machine learning in teaching and learning considering the students background, students past academic score and considering other attributes. As the sizes of classes are large, it would be difficult to assist each individual student in each open learning course, this can increase the bar of the dropout rate at the end of the course. In this paper we are implementing linear regression which is a machine learning algorithm to predict the student’s performance in academics
用线性回归预测学生成绩
本文是关于机器学习的应用如何在教学和学习方面产生巨大的影响,以进一步改善高等教育的学习环境。由于学生对在线和数字课程的兴趣迅速增加,课程时代、Udemy等网站变得非常有影响力。考虑到学生的背景、学生过去的学习成绩和其他属性,我们在教学和学习中实现了机器学习的新应用。由于班级规模大,很难在每一门开放学习课程中帮助每一个学生,这可能会增加课程结束时的辍学率。在本文中,我们正在实现线性回归,这是一种机器学习算法来预测学生在学术上的表现
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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