Utilizing Web Analytics in the Context of Learning Analytics for Large-Scale Online Learning

被引:0
作者
Robloff, Tobias [1 ]
Oldag, Soren [1 ]
Renz, Jan [1 ]
Meinel, Christoph [1 ]
机构
[1] Hasso Platmer Inst, Potsdam, Germany
来源
PROCEEDINGS OF 2019 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE (EDUCON) | 2019年
关键词
Learning Analytics; Web Analytics; Learning Dashboards; MOOCs; Online Learning Environments;
D O I
10.1109/educon.2019.8725118
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Today, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners' interactions on online learning platforms. Although the foundation of both methods is similar, WA has not been profoundly used for LA purposes. However, especially large-scale online learning environments may benefit from WA as it is more sophisticated and well-established in comparison to LA. Therefore, this paper aims to examine to what extent WA can be utilized in this context, without compromising the learners' data privacy. For this purpose, Google Analytics was integrated into the Massive Open Online Course platform of the Hasso Plattner Institute as a proof of concept. It was tested with two deployments of the platform: openHPI and openSAP, where thousands of learners gain academic and industry knowledge about engineering education. Besides capturing behavioral data, the platforms' existing LA dashboards were extended by WA metrics. The evaluation of the integration showed that WA covers a large part of the relevant metrics and is particularly suitable for obtaining an overview of the platform's global activity, but reaches its limitations when it comes to learner-specific metrics.
引用
收藏
页码:296 / 305
页数:10
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