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Indonesian Question Generation Based on Bloom's Taxonomy Using Text Analysis

机译:基于布鲁姆分类法的文本分析印尼问题生成

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Automation of question generation from a text has been one of the focus of research in recent years. In the education field, question generation can be used to assist in the generation of questions to be used as evaluations of learning outcomes. The process of generating questions with different difficulty levels manually is not easy. Firstly, someone must understand the whole matter and then she or he is able to make questions according to the material. Generation of questions in large quantities and various learning materials will certainly require lot of effort and time. Therefore, it is necessary to automate the process of generating the question. This research introduces question generation automation methods based on Bloom's Taxonomy using text analysis. The method proposed in this study yielded an accuracy of 81.35%. The accuracy proves that the proposed method can be used to generate questions automatically.
机译:从文本自动生成问题一直是近年来研究的重点之一。在教育领域,问题生成可用于协助生成问题,以评估学习成果。手动生成具有不同难度级别的问题的过程并不容易。首先,某人必须了解整个问题,然后他或他才能根据材料提出问题。大量生成问题和各种学习材料无疑将需要大量的精力和时间。因此,有必要使问题的生成过程自动化。本研究通过文本分析介绍了基于Bloom分类法的问题生成自动化方法。在这项研究中提出的方法产生了81.35%的准确性。准确性证明了该方法可用于自动生成问题。

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