文章基本信息

标题：Improving Quality of Educational Processes Providing New Knowledge Using Data Mining Techniques
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作者：Manolis Chalaris ; Manolis Chalaris ; Stefanos Gritzalis 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2014
卷号：147
页码：390-397
DOI：10.1016/j.sbspro.2014.07.117
语种：English
出版社：Elsevier
摘要：AbstractOne of the biggest challenges that Higher Education Institutions (HEI) faces is to improve the quality of their educational processes. Thus, it is crucial for the administration of the institutions to set new strategies and plans for a better management of the current processes. Furthermore, the managerial decision is becoming more difficult as the complexity of educational entities increase. The purpose of this study is to suggest a way to support the administration of a HEI by providing new knowledge related to the educational processes using data mining techniques. This knowledge can be extracted among other from educational data that derive from the evaluation processes that each department of a HEI conducts. These data can be found in educational databases, in students’ questionnaires or in faculty members’ records. This paper presents the capabilities of data mining in the context of a Higher Education Institute and tries to discover new explicit knowledge by applying data mining techniques to educational data of Technological Educational Institute of Athens. The data used for this study come from students’ questionnaires distributed in the classes within the evaluation process of each department of the Institute.
关键词：Data mining techniques;Higher Education Institutes;Educational Processes;Educational Data Mining;Decision support;CRISP-DM methodology