A feature-based analysis of MOOC for learning analytics

J. Chauhan, A. Goel
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引用次数: 4

Abstract

Massive Open Online Course (MOOC) is a popular way for offering online courses, globally, by the education providers. With large number of learners enrolled in the courses, it becomes difficult to help the learners, individually, in achieving learning objectives. But, large amount of data gets generated from activities performed by the learner. Learning analytics uses the learner-generated educational data to improve the learning process. Currently, MOOCs provide limited support to the learners for learning analytics. In this paper, an analysis of features offered to the learners by different MOOC platforms for learning analytics, is presented. For this, features of several key platforms are identified and further categorized for analysis purposes. The comparative analysis helps during selection of a platform on basis of the analytical features supported by them. Also, a recommendation is provided for enhancement of learning analytics capabilities of MOOC platforms.
基于特征的MOOC学习分析
大规模在线开放课程(MOOC)是全球教育提供商提供在线课程的一种流行方式。由于大量的学习者参加了课程,因此很难单独帮助学习者实现学习目标。但是,大量的数据是由学习者执行的活动产生的。学习分析使用学习者生成的教育数据来改进学习过程。目前,mooc为学习者提供的学习分析支持有限。本文分析了不同MOOC平台为学习者提供的学习分析功能。为此,本文确定了几个关键平台的特性,并对其进行了进一步分类,以便进行分析。对比分析有助于根据平台所支持的分析特性来选择平台。同时,对MOOC平台学习分析能力的增强提出了建议。
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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