介绍教育数据挖掘的特殊部分

T. Calders, Mykola Pechenizkiy
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引用次数: 87

摘要

教育数据挖掘(EDM)是一个新兴的多学科研究领域,在这个领域中,探索来自各种教育信息系统的数据的方法和技术已经发展起来。随着教育数据的日益丰富,EDM既是一门学习科学,也是数据挖掘的一个丰富的应用领域。EDM有助于研究学生如何学习,以及他们学习的环境。它使数据驱动的决策能够改进当前的教育实践和学习材料。我们简要概述了EDM,并介绍了四篇EDM论文,这些论文代表了数据挖掘在教育中的不同应用领域的横切。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Introduction to the special section on educational data mining
Educational Data Mining (EDM) is an emerging multidisciplinary research area, in which methods and techniques for exploring data originating from various educational information systems have been developed. EDM is both a learning science, as well as a rich application area for data mining, due to the growing availability of educational data. EDM contributes to the study of how students learn, and the settings in which they learn. It enables data-driven decision making for improving the current educational practice and learning material. We present a brief overview of EDM and introduce four selected EDM papers representing a crosscut of different application areas for data mining in education.
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