Learning Objectives, Insights, and Assessments: How Specification Formats Impact Design

Learning Objectives, Insights, and Assessments: How Specification Formats Impact Design
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学习目标、见解和评估:规范格式如何影响设计

DOI:
10.1109/tvcg.2021.3114811
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发表时间:
2022
影响因子:
5.2
通讯作者:
Adar, Eytan
Adar, Eytan
中科院分区:
计算机科学1区
文献类型:
--
作者:
Lee-Robbins, Elsie;He, Shiqing;Adar, Eytan

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尽管交流可视化无处不在,但在设计过程中指定交流意图是特别的。无论我们是从一组可视化中进行选择,委托某人制作它们,还是自己创建它们,指定意图的有效方法都可以帮助指导这一过程。理想情况下,我们应该有一种简洁和共享的规范语言。在以前的工作中,我们认为交际意图可以被视为一个学习/评估问题(即,读者应该学习什么,他们应该在什么测试中取得好成绩)。基于学习的规范格式是有联系的(例如,评估源自目标),但有些格式可能更有效地指定交流意图。通过大规模实验,我们研究了三种规格类型:学习目标、洞察力和评估。参与者根据这些规范中的一项,对他们对一系列可视化设计的偏好进行评级。然后,我们评估了这组可视化设计,以评估哪种规格导致参与者更喜欢最有效的可视化。我们发现,虽然所有规范类型都比无规范格式有优势,但每种格式都有自己的优势。研究结果表明,学习目标型规范对被试的视觉化选择有最大的帮助。我们还确定了规格可能不足而评估至关重要的情况。
Despite the ubiquity of communicative visualizations, specifying communicative intent during design is ad hoc. Whether we are selecting from a set of visualizations, commissioning someone to produce them, or creating them ourselves, an effective way of specifying intent can help guide this process. Ideally, we would have a concise and shared specification language. In previous work, we have argued that communicative intents can be viewed as a learning/assessment problem (i.e., what should the reader learn and what test should they do well on). Learning-based specification formats are linked (e.g., assessments are derived from objectives) but some may more effectively specify communicative intent. Through a large-scale experiment, we studied three specification types: learning objectives, insights, and assessments. Participants, guided by one of these specifications, rated their preferences for a set of visualization designs. Then, we evaluated the set of visualization designs to assess which specification led participants to prefer the most effective visualizations. We find that while all specification types have benefits over no-specification, each format has its own advantages. Our results show that learning objective-based specifications helped participants the most in visualization selection. We also identify situations in which specifications may be insufficient and assessments are vital.
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