Rapid development of open educational resources (OER) is often motivated by a new educational paradigm. This paradigm tends to address current challenges such as reusing, goal-oriented remixing, revising, and redistributing OER. This paper proposes a system to automatically remix, which is a step towards automatic course generation. This system uses an agent-based modeling (ABM) approach to profile OER and simulate the process of selecting and linking the appropriate ones. Each resource profile provides us with metadata that shows its domain and is completed using an appropriate ontology before agents’ interactions. ABM enables cooperation between OER to satisfy requirements of the input syllabus. Using the interaction ability, the most compatible agents, which cover the concepts of the input syllabus, can be linked. The efficiency of the proposed method is evaluated through applying the implemented system on two datasets: ARIADNE and SlideShare. In our experimental results on OER related to the domain of e-learning, we report on the system precision and user satisfaction. Our approach is generic; it can be used with any OER repository and any content management system with a free reuse and remix license.

中文翻译：

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使用基于代理的建模对开放式教学资源进行自动面向课程的混音

开放教育资源（OER）的快速发展通常是由一种新的教育范式推动的。这种范例倾向于解决当前的挑战，例如重用，面向目标的重新混合，修订和重新分配OER。本文提出了一种自动重新混音的系统，这是自动生成课程的一步。该系统使用基于代理的建模（ABM）方法来分析OER并模拟选择和链接适当的OER的过程。每个资源配置文件都为我们提供了显示其域的元数据，并在代理进行交互之前使用适当的本体来完成该元数据。ABM使OER之间的合作能够满足输入课程的要求。使用交互功能，可以将涵盖输入课程大纲概念的最兼容的代理进行链接。通过将实现的系统应用于两个数据集：ARIADNE和SlideShare，评估了所提出方法的效率。在与电子学习领域相关的OER实验结果中，我们报告了系统精度和用户满意度。我们的方法是通用的；它可以与任何具有免费重用和重新混合许可证的OER存储库和任何内容管理系统一起使用。