教育数据挖掘:一个整体的观点

Oswaldo Moscoso-Zea, S. Luján-Mora
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引用次数: 5

摘要

数据挖掘(DM)汇集了广泛的技术和算法,可以从数据库中提取知识,以便及时做出决策。DM已被应用于不同的研究领域。一个重要的研究领域是教育。将数据挖掘技术应用于教育领域被称为教育数据挖掘(EDM)。EDM的主要目的是使用不同的技术来分析来自教育机构的数据,例如:预测、聚类、时间序列分析、分类等。本文介绍了电火花加工的整体观点,包括分类算法,方法和工具中使用的电火花加工过程。此外,分析了教育机构中可以改进的流程和指标。本研究涵盖2005年至2015年发表的论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Educational data mining: An holistic view
Datamining (DM) brings together a wide range of techniques and algorithms which allow the extraction of knowledge from databases for timely decision making. DM has been applied to different fields of study. One important research field is Education. Applying DM in education is known as educational datamining (EDM). The main purpose of EDM is to analyze data from educational institutions using different techniques such as: prediction, clustering, time-series analysis, classification, among others. This paper presents an holistic view of EDM including classification of algorithms, methods and tools used in DM processes. Furthermore, processes and indicators that could be improved are analyzed in educational institutions. This study covers papers presented from 2005 to 2015.
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