用机器学习方法研究缺勤与分数的关系:以线性回归分析为例

R. Yadav
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引用次数: 1

摘要

学生旷课是一个国际问题,不仅影响印度学生。本研究主要针对学生的缺课情况和缺课成绩,采用线性回归分析的方法进行研究。线性回归分析是一种很好的机器学习方法。本研究采用描述性、学生t检验、Pearson相关及回归模型进行统计分析。根据本研究的结果,缺勤与成绩之间存在相当大的差异(t-test=-4.06075, p < 0.05)。研究还发现,课堂缺勤与分数呈负相关(r = -0.6088)。为了研究缺课对学生成绩的影响,我们建立了一个回归模型。这项研究将提高人们对不上课的弊端的认识,对学院管理和学生都有好处。
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A Study of Relationship to Absentees and Score Using Machine Learning Method: A Case Study of Linear Regression Analysis
Absenteeism from classrooms amongst students is an international problem that does not only affect Indian students. This research is focuses on absentees of student in class and score and has been carried out by using linear regression analysis. Linear regression analysis is one of excellent method of machine learning. The descriptive, student's t-test, Pearson correlation, and regression models were used in this study's statistical analysis. According to the results of this study, there are considerable variations between absentees and score  (t-test=-4.06075, p < 0.05). The study also discovered that absenteeism from class had a negative link with the score (r = -0.6088) . To investigate the impact of class absentees on student score, a regression model was created. This study will benefit both the college administration and the students by raising awareness of the disadvantages of not attending classes.
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