用数据挖掘方法评估学生学业成绩

Hanife Goker, H. Bulbul, E. Irmak
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引用次数: 16

摘要

数据挖掘是从数据栈中提取有用信息的过程。最常见的应用领域之一是使用分类算法,通过过去的经验来估计未来的事件。在这种情况下,为了预测未来的事件,使用学生背景创建了一个数据仓库,其中包括学生的人口统计、个人、学校和课程信息。在这个数据仓库上使用分类算法,可以开发出对未来进行推理的新应用。本研究的目的是建立学生数据仓库,并利用数据挖掘算法来改进预警系统,以预测学生及其家庭未来的学业成就,并找出影响学生学业成功的主要因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Estimation of Students' Academic Success by Data Mining Methods
Data mining is a process of getting out useful information from data stacks. One of the most common application areas is to use classification of algorithms that estimate the future events by past experiences. In this context, in order to predict future events, a data warehouse is created by using the background of students which includes demographic, personal, school, and course information of students. On this data warehouse by using classification algorithms, new applications which can make inferences for the future could be developed. Aims of this study are to create student data warehouse which can be used data mining algorithms, to improve an early warning system that may estimate students' the future academic successes for students and also for their families and to find out primary factors affecting their academic success.
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