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Web-Based Recommendation System Architecture for Knowledge Reuse in MOOCs Ecosystems

机译:基于Web的MOOC生态系统知识重用的推荐系统架构

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摘要

With the success of MOOCs (Massive Open Online Courses) in recent years and the emergence of several courses in these environments, students face difficulties in choosing the best materials, modules or courses. Some recommendation systems have come up to address such problem. However, they provide recommendation limited to a specific MOOC provider. This work proposes an architecture of a web-based recommendation system to support students in finding suitable courses or materials to reach their interests. In addition, this work will raise the fundamental actors and roles of an underlying software ecosystem (SECO) and relate them to those involved in MOOCs ecosystems. The main motivation is that several elements of such ecosystems derive from virtual learning community ecosystems, failing to reproduce particularities of MOOCs learning community ecosystem. Therefore, the system resulting from this architecture also aims to achieve the knowledge reuse in these MOOCs ecosystems, i.e., demands, improvements and software sharing over the platforms.
机译:近年来,随着MOOC(大规模开放在线课程)的成功以及在这些环境中出现的几门课程的出现,学生在选择最佳的材料,模块或课程时面临困难。一些推荐系统已经提出来解决这样的问题。但是,他们提供的建议仅限于特定的MOOC提供商。这项工作提出了一个基于Web的推荐系统的体系结构,以支持学生找到合适的课程或材料以达到他们的兴趣。此外,这项工作将提高底层软件生态系统(SECO)的基本角色和作用,并将它们与参与MOOC生态系统的人们联系起来。主要动机是这种生态系统的几个要素源自虚拟学习社区生态系统,无法再现MOOC学习社区生态系统的特殊性。因此,由该架构产生的系统还旨在实现在这些MOOC生态系统中的知识重用,即在平台上的需求,改进和软件共享。

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