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Automatic evaluation technique for certain types of open questions in semantic learning systems

机译:语义学习系统中某些类型的公开问题的自动评估技术

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摘要

In this paper, we propose a methodology to enhance the evaluation tools in semantic learning systems. Our proposal’s aim is to evaluate two types of open questions in hybrid exams. The proposed technique in the first type MOQ (Multi Operations Question) uses the matrix concept for fuzzy score. But POQ (Proof Open Question) is more complicated so we use direct connect to learning objects which saved as ontology based. Also take into consideration the dependence among learning objects so we merge the universal ontology with weight matrix. The proposed methodology has been applied to the case study of the mathematical multi operations question and the proof question on a logic course in a hybrid exam.
机译:在本文中,我们提出了一种方法来增强语义学习系统中的评估工具。我们的提案旨在评估混合考试中的两种公开问题。在第一类MOQ(多操作问题)中提出的技术使用矩阵概念进行模糊评分。但是POQ(证明开放问题)更为复杂,因此我们使用直接连接来学习保存为基于本体的学习对象。还考虑学习对象之间的依赖性,因此我们将通用本体与权重矩阵合并。所提出的方法已经应用于混合考试中的逻辑课程中的数学多操作题和证明题的案例研究。

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