基于Petri网扩展的MOOC学习流建模
Modeling MOOC learnflow with Petri net extensions
摘要：
现代高等教育利用MOOC技术。将大规模开放式在线课程（MOOC）的教育过程建模为一个动态的多智能体过程是一项具有挑战性的任务。在本文中，Petri网扩展的学习流建模的背景下进行了研究。它示出了如何learnflow可以与经典和有色Petri网建模。这些扩展有助于对分布式和多代理过程进行建模。然而，现有的Petri网扩展不提供多课程计划和自适应学习的背景下建模的教育过程的能力。我们提出了\emph{Petri nets with reference data}（PNRDs）在MOOC的电子学习建模。PNRD使我们能够以一种直观、清晰和不超载的形式代表教育过程的模型。此外，PNRD使我们能够展示多课程计划的各个方面以及MOOC教育过程中的动态变化。我们还展示了如何PNRD可以用来模拟基于项目的学习中的在线学生协作。
英文摘要：
Modern higher education takes advantage of MOOC technology. Modeling an education process of Massive open online courses (MOOCs) as a dynamic and multi-agent process is one of the challenging tasks. In this paper, Petri net extensions are investigated in the context of the learnflow modeling. It is shown how a learnflow can be modeled with classical and Colored Petri nets. These extensions facilitate modeling distributed and multi-agent processes. However, existing Petri net extensions do not provide the ability to model an education process in the context of multi-course programs and adaptive learning. We propose \emph{Petri nets with reference data} (PNRDs) for modeling e-learning in MOOCs. PNRDs allow us to represent a model of the education process in a visual, clear and not overloaded form. Moreover, PNRDs enable us to display aspects of multi-course programs and dynamic changes in the MOOC education process. We also show how PNRDs can be used to model online student collaboration in project-based learning.
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