测量和挖掘LMS数据

I. Kazanidis, S. Valsamidis, Sotirios Kontogiannis, A. Karakos
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引用次数: 6

摘要

教育内容的质量和数量是决定电子学习成功与否的关键因素。本研究提出了一项建议,使学习者能够评估在线内容及其使用情况。它提出了一些新的内容和课程使用的度量和指标,并通过数据挖掘技术调查了用户的在线行为对他们的表现的影响,因为这反映在课程成绩上。提出的措施和指标在希腊一所大学的案例研究中得到了应用。他们跟踪了课程内容的数量及其相应的使用情况,这反映了用户对学习内容的体验。结果表明,尽管许多措施相关更高年级,在线学习的持续时间,主要影响学习者的最终成绩。因此,在线平台可能会指出活动量低的学生,并向他们发送额外的信息,提醒他们花更多的时间学习在线课程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring and Mining LMS Data
Educational content quality and quantity is a crucial factor for the success of e-learning procedure. This study puts forward a proposal that enables the evaluation of online content and its usage by the learners. It proposes some new measures and metrics for content and course usage and investigates, through data mining techniques, the impact of users' online behavior to their performance as this is reflected by course grade. The proposed measures and metrics were used in the case study of a Greek university. They tracked both course content quantity and its corresponding usage which express user experience over the learning content. The results show that although many measures are related to higher grade, it is the duration of online study that mainly affects learners' final grade. Therefore an online platform may indicate students with low activity and send them additional messages tar on them to study more time the online course.
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