Educational Data Mining and Indian Technical Education System

Nancy Kansal, V. K. Solanki, Vineet Kansal
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Abstract

Educational Data Mining (EDM) is emerged as a powerful tool in past decade and is concerned with developing methods to explore the unique types of data in educational settings. Using these methods, to better understand students and the settings in which they learn. Different unknown patterns using classification, Clustering, Association rule mining, decision trees can be discovered from this educational data which could further be beneficial to improve teaching and learning systems, to improve curriculum, to support students in the form of individual counseling, improving learning outcomes in terms of students' satisfaction and good placements as well. Therefore a literature survey has been carried out to explore the most recent and relevant studies in the field of data mining in Higher and Technical Education that can probably portray a pathway towards the improvement of the quality education in technical institutions.
教育数据挖掘与印度技术教育体系
教育数据挖掘(Educational Data Mining, EDM)是近十年来兴起的一种强大的工具,它涉及开发方法来探索教育环境中独特类型的数据。使用这些方法,可以更好地了解学生和他们学习的环境。利用分类、聚类、关联规则挖掘、决策树等方法,可以从这些教育数据中发现不同的未知模式,从而进一步改善教与学系统,改进课程,以个人辅导的形式支持学生,提高学生的满意度和良好的学习效果。因此,我们进行了一项文献调查,以探索高等技术教育中数据挖掘领域的最新和相关研究,这些研究可能会描绘出一条改善技术院校素质教育的途径。
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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