stickkipedia:解释性类比的搜索引擎和资源库

Varun Kumar, S. Bhat, N. Pedanekar
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引用次数: 0

摘要

粘性学习是指学习者在很长一段时间内保留的学习。好的老师经常使用解释性类比,以一种粘性的方式解释复杂的概念。这种类比通过将一个不熟悉的目标概念映射到一个更熟悉的源概念上来解释它。然而,在教学和学习中使用类比往往依赖于教师个人的想象力或学生主动寻找类比。在本文中,我们提出了一个类比搜索引擎Stickipedia,它可以自动检索在互联网上为搜索目标概念填充的类比。基于对学生的调查,我们还提出了类比的属性,可以帮助学生选择他们喜欢的类比。我们在维基百科中为检索到的类比填充其中的一些属性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stickipedia: A Search Engine and Repository for Explanatory Analogies
Sticky learning refers to learning that is retained by a learner over a long period of time. Explanatory analogies are often used by good teachers to explain complex concepts in a sticky manner. Such analogies explain an unfamiliar target concept by mapping it onto a more familiar source concept. However, the use of analogies in teaching and learning often relies on the imagination of individual teachers or the initiative taken by students in finding them. In this paper, we present Stickipedia, an analogy search engine that automatically retrieves analogies populated on the internet for a searched target concept. Based on a student survey, we also suggest attributes of analogies which could aid students in choosing the analogies they prefer. We populate some of these attributes in Stickipedia for the retrieved analogies.
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