教育数据挖掘中的模式追求是对学生隐私的威胁

IF 2.7 Q1 EDUCATION & EDUCATIONAL RESEARCH
Kyriaki H. Kyritsi, Vassilios Zorkadis, E. C. Stavropoulos, Vassilios S. Verykios
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引用次数: 12

摘要

最近的技术进步带来了巨大的收集、存储和分析数据的能力,这些数据以越来越快的速度从不同的来源产生。提供开放和远程学习课程的学术机构,如希腊开放大学(Hellenic open University),可以从与学生信息和通信系统相关的大数据中受益,并使用现代技术和大数据分析工具,前提是学生的隐私权不会受到损害。通过匿名化方法可以达到数据挖掘和维护隐私之间的平衡,但另一方面,这种方法也带来了一些技术问题,例如原始数据中发现的一定量信息的丢失。考虑到学习过程是一个相互作用的角色和因素的框架,在这个系统中发现模式首先对学习者来说是非常有用和有益的,而且,能够发布和分享这些结果将对整个学术机构非常有帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Pursuit of Patterns in Educational Data Mining as a Threat to Student Privacy
Recent technological advances have led to tremendous capacities for collecting, storing and analyzing data being created at an ever-increasing speed from diverse sources. Academic institutions which offer open and distance learning programs, such as the Hellenic Open University, can benefit from big data relating to its students’ information and communication systems and the use of modern techniques and tools of big data analytics provided that the student’s right to privacy is not compromised. The balance between data mining and maintaining privacy can be reached through anonymisation methods but on the other hand this approach raises technical problems such as the loss of a certain amount of information found in the original data. Considering the learning process as a framework of interacting roles and factors, the discovery of patterns in that system can be really useful and beneficial firstly for the learners and furthermore, the ability to publish and share these results would be very helpful for the whole academic institution.
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来源期刊
Journal of Interactive Media in Education
Journal of Interactive Media in Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
6.40
自引率
6.70%
发文量
8
审稿时长
16 weeks
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