面向自适应网络学习的协同元数据充实

Róbert Móro, Ivan Srba, Maros Uncík, M. Bieliková, Marián Simko
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引用次数: 7

摘要

近年来,我们见证了Web 2.0的扩展。它的主要特点是允许用户通过各种方式协作创建内容,例如注释、讨论、wiki、博客或标签。这种方法也影响了基于网络的学习,为此引入了术语“学习2.0”。在本文中,我们探索在这样的系统中使用标签。标签可用于改进搜索、web文档的分类、创建大众分类法和本体或增强用户模型。标签的另一个方面是它们作为资源和用户之间的桥梁来创建一个社交网络。我们将标签整合到一个学习框架ALEF中,并通过实验评估了标签在教育过程中的使用情况。
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Towards Collaborative Metadata Enrichment for Adaptive Web-Based Learning
In recent years we have witnessed expansion of Web 2.0. Its main feature is allowing users' collaboration in content creation using various means, e.g. annotations, discussions, wikis, blogs or tags. This approach has influenced also web-based learning, for which the term "Learning 2.0" has been introduced. In this paper we explore using tags in such systems. Tags can be used for improving of searching, categorization of web-documents, creating folksonomies and ontologies or enhancing the user-model. Another aspect of tags is that they act as a bridge between resources and users to create a social network. We integrated tags in a learning framework ALEF and experimentally evaluated their usage in education process.
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