Refined Distractor Generation with LSA and Stylometry for Automated Multiple Choice Question Generation
Refined Distractor Generation with LSA and Stylometry for Automated Multiple Choice Question Generation
复制标题
使用 LSA 和 Stylometry 生成精致的干扰项，用于自动生成多项选择题
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Wei Liu
中科院分区：
文献类型：
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作者：
Josef Moser;Christian Gütl;Wei Liu
随着终身学习在我们的社会中变得越来越重要，必须提供允许学生评估其进步的机制。一种常用且被广泛接受的反馈机制是多项选择测试。手动创建多项选择题通常是一个耗时的过程，涉及多次反复试验和错误。近年来，使用文本处理和自然语言处理技术，自动生成多项选择题比以往任何时候都更加接近现实。然而，手动创建和自动生成此类测试中最困难的任务之一是创建干扰项，因为不合适的干扰项会让学生轻松猜测正确答案，从而抵消了这些问题的目标。在本文中，我们研究了干扰项的所需属性，并确定了相关的文本处理算法，特别是用于干扰项选择的潜在语义分析和文体测量算法。将精炼后的干扰器与我们现有的自动问题创建器 (AQC) 生成的基线干扰器进行比较。我们的初步评估表明，这种新颖的组合方法产生的干扰物质量比基线 AQC 系统的干扰物质量更高。
As lifelong learning becomes increasingly important in our society, mechanisms allowing students to evaluate their progress must be provided. A commonly used and widely accepted feedback mechanism is the multiple-choice test. Manual creation of multiple choice questions is often a time consuming process involving many iterations of trail and error. Using text processing and natural language processing techniques, automated multiple choice question generation, in recent years, is getting much closer to reality than ever. However, one of the most difficult tasks in both manual creation and automated generation of this kind of tests is the creation of distractors, because unsuitable distractors allow students to easily guess the correct answer, which counteracts the goal of these questions. In this paper, we investigated the desired properties of distractors and identified relevant text processing algorithms, specifically, latent semantic analysis and stylometry, for distractor selection. The refined distrators are compared with baseline distrators generated by our existing Automated Question Creator (AQC). Our preliminary evaluation shows that this novel combined approach produces distractors with a higher quality than those of the baseline AQC system.