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Quality Assurance for Reusable Learning Objects on a Peer-To-Peer Network

机译:对等网络上可重用学习对象的质量保证

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In this research, improving on the quality of Reusable Learning Objects (RLOs) on a Peer-To-Peer (P2P) network is considered. The RLO was first redesigned to have a fundamentally inherent pedagogical structure, which gave it an immediate foundational level of quality in terms of opportunities related to reusability. Applying the Learning Object Review Instrument 1.5 (LORI 1.5) demonstrated that some of the elements are inherent in this new RLO design, so there was no need to constantly have such features evaluated with LORI. A modified LORI was therefore developed in order to evaluate the remaining features of the RLO. The research identified these remaining elements to produce a Review Rubric for scoring the RLO’s quality. In addition, an algorithm is given which considers one or more subject-matter experts as part of a review process. Utilizing the subject-matter experts in a P2P network involved the creation of special nodes to ensure data integrity and post-availability of the review scores for RLOs. The research concludes that the redesigned RLOs along with the corresponding Review Rubric and scoring algorithm produces a system suitable for a P2P network, where for the first time, RLOs can be shared of assured quality to promote eLearning within P2P networks.
机译:在这项研究中,考虑了提高对等(P2P)网络上的可重用学习对象(RLO)的质量。 RLO最初经过重新设计,具有根本上固有的教学结构,这使它在与可重用性相关的机会方面具有了基本的质量基础。应用学习对象评审工具1.5(LORI 1.5)证明了此新RLO设计中固有的某些元素,因此无需经常使用LORI评估这些功能。因此,开发了改良的LORI,以评估RLO的其余功能。该研究确定了这些剩余要素,从而形成了用于评估RLO质量的评论专栏。另外,给出了一种算法,该算法将一个或多个主题专家视为审阅过程的一部分。利用P2P网络中的主题专家来创建特殊节点,以确保RLO的数据完整性和评论分数的后可用性。研究得出的结论是,重新设计的RLO以及相应的Review Rubric和评分算法产生了一个适用于P2P网络的系统,在该系统中,RLO首次可以共享有保证的质量,以在P2P网络中促进电子学习。

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