面向价值发现的学习资源描述方案：以LRMI元数据为例

A Value-finding Oriented Scheme for Specifying Learning Resources: Taking LRMI As an Example

随着信息技术和开放理念在资源领域的发展，如何构建良好资源生态，挖掘潜在价值成为资源建设与应用中一个研究热点。从强调“内容为王”到关注“情境为上帝”业已成为数字化资源的价值取向。在教育资源领域，应用元数据标记以实现资源在网络中的可发现性，追求“价值发现”已经成为教育资源库建设的新目标，期望从“人找资源”变为“资源随人”。LRMI元数据是面向价值发现的学习资源描述方案的典范，它对三大搜索引擎巨头Google、Yahoo、Bing发起的Schema.org元数据词汇框架进行拓展，以提供符合教育特定需求的术语，同时增加资源在网络中的可发现性，优化资源的搜索结果。该文论述了当前学习资源价值的新诉求，以LRMI案例作为代表，总结了当前资源搜索的现实需求，分析了LRMI元数据的工作机制和当前学习资源库建设中的元数据描述方案。在LRMI中，元数据实现了对资源的基本描述，而伴生数据则通过提供额外的情境信息，与元数据相互补充共同完成了对资源的完整表示。同时，连通利益相关者、学习资源、学习注册中心、情境信息构成一个良好生态系统，也为未来学习分析和开放教育资源发展提供了潜在的解决方案。

In recent years， the value of educational resource has been shifting from “content is King” to “context is the God”. Using metadata to facilitate the discovery of online resources and construct value-finding paradigm has aroused continued attention in educational resource development for the purpose of leading traditional “people finding resources” mode to “resources following people” way. LRMI metadata is the representative in value-finding oriented scheme for specifying learning resources， which extends the Schema.org metadata vocabulary initiated by the search engines Google， Yahoo and Bing in order to meet educational specific needs， enhancing discoverability and optimizing search. This article starts with introducing new value proposition， then analyzes requirements， mechanism and schema in LRMI metadata. Furthermore， bridging stakeholders， learning resources， learning registry and learning context would help to build a good ecosystem which also provides a potential support for learning analysis and open educational resource research.