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Building a Multiple Linear Regression Model to Predict Students' Marks in a Blended Learning Environment

机译:构建多元线性回归模型,以预测混合学习环境中的学生标记

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This research attempts to build a multiple linear regression model to predict the marks of students. As a case study, the course M359 - Relational Database offered to undergraduate students of Arab Open University, Oman is taken. The model is trained using the different assessment marks of students in blended learning mode of the above course. Separate models were built based on the gender. Same datasets were used for training and testing purposes. The open source statistical software gretl was used to build and test the model. The study found that the model generated for male category shows more correlation in the process of prediction than the female category. The findings of the research suggest that it is challenging to build a prediction model for students in blended learning environment.
机译:该研究试图建立一个多线性回归模型来预测学生的标志。作为一个案例研究,课程M359 - 关于阿拉伯公开大学本科生的关系数据库,阿曼被采用。该模型使用上述课程的混合学习模式中的学生的不同评估标志进行培训。基于性别建立了单独的模型。相同的数据集用于培训和测试目的。开源统计软件GRETL用于构建和测试模型。该研究发现,对于男性类别生成的模型显示了比女性类别的预测过程中的更多相关性。该研究的结果表明,建立混合学习环境中的学生预测模型是挑战性的。

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