识别学生成绩预测的关键特征

Jiaqi Cui, Yupei Zhang, Rui An, Yue Yun, Huan Dai, Xuequn Shang
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引用次数: 1

摘要

随着教育数据挖掘的发展和教务数据的积累,可以从不同的角度分析学生在学校的表现,探索影响学生成绩的更宝贵的方面。我们的研究对学生的基础课程信息、学习行为信息和录取信息进行数据挖掘,有助于找到它们之间的关系。本研究主要探讨影响学生学习成绩的关键因素。然后,本研究考虑识别学生行为与成绩之间的关系。通过使用先进的机器学习方法和特征分析方法LASSO,该工作对学生行为的最重要特征进行了评级。我们发现学生的行为和他们的成绩之间有几个关键的关系,例如,一个人借的书越多,他/她的成绩就越好。本研究有助于教育工作者和学生更好地理解内涵因素与学生成绩之间的关系。
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Identifying Key Features in Student Grade Prediction
With the development of education data mining and the data of academic affairs accumulated, the performance of students in school could be analyzed from different views and explore more precious aspects which influence the grades of students. Our research conducts data mining on student basic courses information, learning behavior information and admission information, which will help to find the relationship between them. This work mainly focus on exploring the key features that take the important roles in student academic performance. Then the work takes the consider of identifying the relationship between student behaviors and their grades. By using the advanced machine learning methods and feature analysis methods, LASSO, the work rated the most important features of student behaviors. We found several key relationships between student behaviors and their grades, for example, the more books one borrows, the better grade he/she will get. This work would help the educators and students to better understand the relationship between connotative factors and the student achievement.
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