元数据的组合使用改善学习体验

Martin Memmel, Rafael Schirru, M. Wolpers, Eleftheria Tomadaki
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引用次数: 2

摘要

今天,用户不仅可以访问存储在传统资源库中的学习资源。他们使用任何一种数字资源,通常是在社交媒体平台的背景下产生的。当试图改善学习体验时,至关重要的是所有潜在有用的资源都是可访问的;并且资源的描述方式允许识别哪些是相关的。我们建议通过结合专家生成的元数据、用户交互、观察组件和机器生成的元数据来丰富学习资源描述。我们给出了一个简单的例子,通过将社交媒体平台ALOE与来自阿里阿德涅知识库和公共FlashMeeting重播的资源和元数据集成来编译丰富的元数据集。
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Towards the Combined Use of Metadata to Improve the Learning Experience
Today, users do not only access learning resources stored in traditional repositories. They use any kind of digital resource, often generated in the context of social media platforms. When trying to improve the learning experience, it is crucial that all resources that are potentially useful are accessible; and that the resources are described in a way that allows to identify what is relevant. We suggest enriching learning resource descriptions by combining metadata generated by experts, user interactions, observation components and machine-generated metadata. We give a brief example of the compilation of rich metadata sets by integrating the social media platform ALOE with resources and metadata from the Ariadne knowledge pool and public FlashMeeting replays.
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