CHS: Small: Using Learning Objectives for Visualization Design

信息可视化主要有两种类型：一种是用来发现洞察力的，另一种是用来进行交流的。虽然交际形式更为常见，但大多数研究都集中在洞察力发现类型上。对于通信可视化的设计者来说，这是一个问题，他们没有一套很好的工具来测试他们的设计目标是否得到了满足。具体地说，很难回答这个问题：可视化的查看者是否从可视化中学到了什么，或者他们只是“读了就忘了它”？由于没有更好的方法来描述他们的具体目标和评估成功，可交流的可视化设计者通常依赖于关于图表类型、编码、叙事技巧和其他设计元素的通用启发式建议来使用。该项目旨在创建方法和工具，以帮助设计者在学习目标方面具体定义他们的目标，以及确定目标是否达到的测试和工具。反过来，这应该会提高数字和图形素养，并加强对从新闻到金融等领域的复杂信息的理解。这项研究将支持不断增长的工作类别，包括可视化设计师、计算记者和数据分析师，以及专注于公共沟通的组织。项目活动还将为本科生、研究生和专业人员提供研究和实践培训，同时项目成果将被纳入视觉化课程的可用教材，并作为探索性数据分析、计算新闻和医学传播等相关课程的模块。要提供一个学习目标和测试框架来构建交流性可视化，需要对设计者如何以及为什么构建他们的可视化有深刻的理解。具体地说，该项目的目标是(A)开发一种用于描述交流意图的学习目标“语言”(例如，“观众将能够描述房价/租金比数据中的不同类型的趋势”)，(B)设计正确有效的测试机制以确保实现这些目标(例如，“根据价格/租金比，以下哪个城市呈现‘泡沫’模式？”)，以及(C)提供工具--包括工作流程和软件--帮助设计人员为读者创建学习目标和测试。以及对其可视化的评估。通过强调构建可视化的学习目标，设计师将更有信心地相信，他们预期的信息是通过设计传达的，而指标预测这些设计将更成功地传达该信息。即使没有一种设计在所有目标上都是最优的，权衡也会更加突出，更容易理解，让设计师做出更好的决定。虽然这项工作的重点是用于更广泛的公众消费的静态交流可视化，如与新闻故事相关的数据，但这项研究可以扩展到其他应用，包括交互式可视化、视觉分析系统、数字和纸质教科书中的解释性和教育性图形，以及以专家为中心的形式，如科学文件或公司报告中的图形。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

There are two main types of information visualizations: those used to find insights, and those used to communicate them. While the communicative form is far more common, most research has focused on the insight-finding type. This is problematic for designers of communicative visualization who do not have a great set of tools to test if their design goals are being met. Specifically, it is difficult to answer the question: did the viewer of the visualization learn anything from the visualization or did they simply "read it and forget it?" Without better ways to describe their specific goals and evaluate success, communicative visualization designers often rely on generic heuristic advice about chart types, encodings, narrative techniques, and other design elements to use. This project seeks to create methods and tools for helping designers concretely define their goals in terms of learning objectives, as well as tests and tools to determine if the objectives are met. This, in turn, should improve numerical and graphical literacy as well as enhanced understanding of complex information in domains from news to finance. The research will support growing job categories including visualization designers, computational journalists, and data analysts, as well as organizations focused on public communication. The project activities will also provide research and practical training for undergraduates, graduates, and professionals, while project results will be integrated into accessible educational materials for both visualization-specific classes and as modules for related courses in, e.g., exploratory data analysis, computational journalism, and medical communication. Providing a learning-objective and testing framework for building communicative visualizations requires a deep understanding of how and why designers build their visualizations. Specifically, the goals of this project are (a) developing a learning-objectives "language" for describing communicative intent (e.g., "the viewer will be able to describe the different kinds of trends in the price-rent ratio data"), (b) designing correct and effective testing mechanisms to ensure that these objectives are achieved (e.g., "Based on the price-rent ratio, which of the following cities is displaying a 'bubble' pattern?"), and (c) providing tools -- both workflows and software -- to help designers create learning objectives and tests for readers, as well as for the evaluation of their visualizations. By emphasizing learning objectives for building visualizations, designers will have more confidence that their intended message is communicated by designs that metrics predict will be more successful in communicating that message. Even when no design is optimal across all objectives, the trade-offs will be more salient and easier to understand, allowing designers to make better decisions. Although the focus of this work is on static communicative visualizations for broader public consumption, such as data associated with news stories, the research can be extended to other applications including interactive visualizations, visual analysis systems, explanatory and educational graphics in digital and paper textbooks, and expert-focused forms such as graphics in scientific documents or corporate reports.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.