带有标签连词的自由形式图的自动分级

N. Smith, P. Thomas, K. Waugh
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引用次数: 5

摘要

自由格式答案的自动评分越来越重要。本文提出了我们所知道的唯一能够自动评分自由格式图表答案的系统。我们的方法识别在该领域中具有特定意义的图的部分,称为最小有意义单元(mmu),并将它们与模型解决方案中的等效部分相匹配。匹配的结果用于计算分数,并产生适当的反馈。学生答案中的错误、遗漏和多余的项目使匹配变得复杂。特别是,图中的继承层次结构可能导致图中的标签在多个对象之间分散。我们的方法已经成功地应用于各种图表类型和等级图表,比人类标记更好。我们简要描述了一组工具,这些工具允许轻松创建适合在线评估和嵌入到VLE测验引擎中的问题、标记方案和图表编辑器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Grading of Free-Form Diagrams with Label Hypernymy
The automatic grading of free-form answers is gaining importance. This paper presents the only system we know of capable of automatically grading free-form diagrammatic answers. Our approach identifies the parts of a diagram that carry specific meaning in that domain, termed minimal meaningful units (MMUs), and matches them with equivalent parts in a model solution. The result of the matching is used to calculate the grade and to generate appropriate feedback. The matching is complicated by errors, omissions, and superfluous items in the student answer. In particular, inheritance hierarchies in diagrams can cause labels in the diagram to be fragmented across several objects. Our approach has been successfully applied to a variety of diagram types and grades diagrams better than a human marker. We briefly describe a set of tools that allow the easy creation of questions, marking schemes, and diagram editors suitable for online assessment and embedding in a VLE quiz engine.
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