Argumentation Scheme-Based Argument Generation to Support Feedback in Educational Argument Modeling Systems
Argumentation Scheme-Based Argument Generation to Support Feedback in Educational Argument Modeling Systems
复制标题
基于论证方案的论证生成支持教育论证建模系统中的反馈
DOI：
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发表时间：
2016
影响因子：
4.9
通讯作者：
N. Green
中科院分区：
文献类型：
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作者：
N. Green
本文描述了一个教育论证建模系统GAIL（Genetics Argumentation Inquiry Learning）。使用GAIL的图形界面，学习者可以从可能的论点内容元素（假设，数据等）中进行选择。显示在屏幕上，用于构建参数图。与以前的系统不同，GAIL使用独立于领域的论证方案来生成专家论证作为知识源。通过将学习者的论点图与生成的论点进行比较，GAIL可以提供关于学习者论点的结构和含义的特定问题反馈，例如，学习者的论证包含了一个无关的前提。为了生成论证，论证方案从课程作者指定的因果域模型实例化。因此，这种生成专家论证的方法具有在其他领域使用的潜力。在本文中，我们描述了使用GAIL的创作工具来创建领域模型和内容元素提供一个特定的教训，如何在GAIL专家参数生成，以及如何产生的反馈。由于GAIL是一个正在进行的工作，本文还描述了下一个设计迭代的计划。
This paper describes an educational argument modeling system, GAIL (Genetics Argumentation Inquiry Learning). Using GAIL’s graphical interface, learners can select from possible argument content elements (hypotheses, data, etc.) displayed on the screen with which to construct argument diagrams. Unlike previous systems, GAIL uses domain-independent argumentation schemes to generate expert arguments as a knowledge source. By comparing the learner’s argument diagram to a generated argument, GAIL can provide problem-specific feedback on both the structure and meaning of the learner’s argument, e.g., that the learner’s argument contains an irrelevant premise. To generate arguments, the argumentation schemes are instantiated from causal domain models specified by lesson authors. Thus, this approach to generating expert arguments has the potential to be used in other domains. In this paper we describe use of GAIL’s Authoring Tool to create the domain model and content elements to be provided for a specific lesson, how expert arguments are generated in GAIL, and how the feedback is produced. As GAIL is a work-in-progress, the paper also describes plans for the next design iteration.