Educational data mining in the academic setting: employing the data produced by blended learning to ameliorate the learning process

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Data Technologies and Applications Pub Date : 2022-12-23 DOI:10.1108/dta-06-2022-0252
Konstantinos Chytas, A. Tsolakidis, Evangelia Triperina, C. Skourlas
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引用次数: 2

Abstract

PurposeThe purpose of this paper is to introduce an interactive system that relies on the educational data generated from the online Universities services to assess, correct and ameliorate the learning process for both students and faculty.Design/methodology/approachIn the presented research, data from the online services, provided by a Greek University, prior, during and after the COVID-19 outbreak, are analyzed and utilized in order to ameliorate the offered learning process and provide better quality services to the students. Moreover, according to the learning paths, their presence online and their participation in the services of the University, insights can be derived for their performance, so as to better support and assist them.FindingsThe system can deduce the future learning progression of each student, according to the past and the current performance. As a direct consequence, the exploitation of the data can provide a road map for the strategic planning of universities, can indicate how the learning process can be updated and amended, both online and in person, as well as make the learning experience more essential, effective and efficient for the students and aiding the professors to provide a more meaningful and to-the-point learning experience.Originality/valueNowadays, educational activities in academia are strongly supported by online services, information systems and online educational materials. The learning design in the academic setting is primarily facilitated in the University premises. However, the exploitation of the contemporary technologies and supporting materials that are available online can enrich and transform the educational process and its results.
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学术环境中的教育数据挖掘:利用混合学习产生的数据来改善学习过程
本文的目的是介绍一个交互式系统,该系统依赖于在线大学服务产生的教育数据来评估、纠正和改善学生和教师的学习过程。设计/方法/方法在本研究中,分析和利用了一所希腊大学在COVID-19爆发之前、期间和之后提供的在线服务数据,以改善所提供的学习过程,并为学生提供更优质的服务。此外,根据他们的学习路径、他们在网上的存在以及他们对大学服务的参与,可以对他们的表现得出见解,从而更好地支持和帮助他们。该系统可以根据每个学生过去和现在的表现推断出未来的学习进度。直接的结果是,数据的利用可以为大学的战略规划提供路线图,可以指示如何更新和修改学习过程,无论是在线还是面对面,以及使学习体验对学生来说更加重要,有效和高效,并帮助教授提供更有意义和更直接的学习体验。创意/价值如今,学术界的教育活动得到了在线服务、信息系统和在线教育材料的大力支持。学术环境中的学习设计主要是在大学校园内进行的。然而,利用现代技术和在线支持材料可以丰富和改变教育过程及其结果。
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来源期刊
Data Technologies and Applications
Data Technologies and Applications Social Sciences-Library and Information Sciences
CiteScore
3.80
自引率
6.20%
发文量
29
期刊介绍: Previously published as: Program Online from: 2018 Subject Area: Information & Knowledge Management, Library Studies
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