A data mining approach for forecasting students' performance

M. C. Nicoletti, M. Marques, M. Guimaraes
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引用次数: 3

Abstract

Educational Data Mining (EDM) is a research area with focus on the use of data mining algorithms/techniques in educational data, with a diversified range of purposes. Among them, EDM can be useful for inducing a model to forecast students' final performance, early in the term, in time to trigger the use of educational recovery techniques, in an attempt to prevent students' failures. This paper presents and discusses the results of three experiments on forecasting students' performance, based on real data, extracted from stored students' performance records related to an university course.
预测学生成绩的数据挖掘方法
教育数据挖掘(EDM)是一个研究领域,重点是在教育数据中使用数据挖掘算法/技术,具有多种用途。其中,EDM可以用来建立一个模型来预测学生的期末表现,在学期早期,及时触发教育恢复技术的使用,以防止学生的失败。本文介绍并讨论了基于实际数据的三个预测学生成绩的实验结果,这些数据提取自与大学课程相关的存储学生成绩记录。
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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