moocRP:一个开源分析平台

Z. Pardos, Kevin Kao
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引用次数: 35

摘要

在本文中,我们通过引入一个开源的、基于网络的数据存储库和分析工具来解决透明度、模块化和隐私问题,该工具是为大规模开放在线课程社区量身定制的。该工具集成了数据请求/授权和分发工作流,以及简单的分析模块上传格式,以便在教师和研究人员之间重用和复制分析结果。我们调查了竞争数据模型的发展情况,所有这些都可以在平台中容纳。数据模型描述提供给分析作者,他们可以根据自己的需求和特定数据模型的扩展情况,选择编写任意数量的数据模型,这与智能手机应用程序商店非常相似。本文描述了分析和交互可视化的两个案例研究实例。其结果是一种简单而有效的学习分析方法,可立即适用于X财团机构及其他机构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
moocRP: An Open-source Analytics Platform
In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflows as well as a simple analytics module upload format to enable reuse and replication of analytics results among instructors and researchers. We survey the evolving landscape of competing data models, all of which can be accommodated in the platform. Data model descriptions are provided to analytics authors who choose, much like with smartphone app stores, to write for any number of data models depending on their needs and the proliferation of the particular data model. Two case study examples of analytics and interactive visualizations are described in the paper. The result is a simple but effective approach to learning analytics immediately applicable to X consortium institutions and beyond.
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