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

机译:利用Web Analytics在学习分析的上下文中进行大规模在线学习

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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.
机译:如今,Web Analytics(WA)通常用于获取有关用户及其在网站上的行为的关键信息。此外,随着在线学习的兴起,学习分析(LA)被出现为一个单独的研究领域,用于收集和分析在线学习平台上的学习者的互动。虽然两种方法的基础是类似的,但是WA尚未用于LA目的。然而,特别是大规模的在线学习环境可能从WA受益,因为与LA相比,它更复杂和更良好。因此,本文旨在检验在此背景下可以在多大程度上使用,而不会影响学习者的数据隐私。为此目的,Google Analytics被纳入了哈索普拉特纳研究所的大规模开放的在线课程平台,作为概念证明。它通过平台的两个部署测试了:Openhpi和Opensap,数千名学习者获得了有关工程教育的学术和行业知识。除了捕获行为数据外,Pervices的Plations的现有LA仪表板还由WA指标扩展。对整合的评估显示,WA涵盖相关指标的大部分,特别适用于获得平台的全球活动的概述,而是达到学习者特定度量的局限性。

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