【24h】

Putting adaptive granularity and rich context into learning objects

机译:将自适应粒度和丰富上下文放入学习对象中

获取原文
获取原文并翻译 | 示例

摘要

The content granularity and context information are two important factors to the efficiency and reusability of learning objects. The context information is necessary to facilitate the discovery and reuse of learning objects stored in global and/or local repositories. However, traditional learning objects are generally not conceived to incorporate with enough context information. Users have to do some extension of the description item set to fit their special use. In this paper, in order to deal with the issue mentioned above, we firstly introduce a context-rich paradigm, the related service driven tagging strategy, and a context model of learning objects. We further explain how to use the context information to realize the adaptive granularity of the content object. Finally, we show a simple concept model for online authoring systems that support the evolution from resource objects to learning objects.
机译:内容粒度和上下文信息是影响学习对象的效率和可重用性的两个重要因素。上下文信息对于促进发现和重用存储在全局和/或本地存储库中的学习对象是必需的。但是,通常不认为传统的学习对象会包含足够的上下文信息。用户必须对描述项集进行某种扩展以适合他们的特殊用途。在本文中,为了解决上述问题,我们首先介绍了一种上下文丰富的范式,相关的服务驱动的标记策略以及学习对象的上下文模型。我们进一步说明如何使用上下文信息来实现内容对象的自适应粒度。最后,我们展示了一个在线创作系统的简单概念模型,该模型支持从资源对象到学习对象的演变。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号