学习可视化工具:教学数据可视化教程

Leo Yu-Ho Lo, Yao Ming, Huamin Qu
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引用次数: 9

摘要

教学和倡导数据可视化是可视化社区中最重要的活动之一。随着商业和科学专业人士对数据分析的兴趣日益浓厚,数据可视化课程吸引了来自不同学科的学生。然而,全面的可视化训练要求学生对编程有一定的熟练程度,这一要求对教师和学生都提出了挑战。随着可视化工具的最新发展,我们已经通过教授广泛的可视化和支持工具来克服这些障碍。从基于gui的可视化工具和使用Python进行数据分析开始,学生们将可视化知识运用到越来越多的编程实践中。在课程结束时,学生可以用D3和其他基于编程的可视化工具设计和实现可视化。在整个教学过程中,我们不断收集学生反馈,不断完善教材。本文阐述了我们在设计教材时的教学方法和考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning Vis Tools: Teaching Data Visualization Tutorials
Teaching and advocating data visualization are among the most important activities in the visualization community. With growing interest in data analysis from business and science professionals, data visualization courses attract students across different disciplines. However, comprehensive visualization training requires students to have a certain level of proficiency in programming, a requirement that imposes challenges on both teachers and students. With recent developments in visualization tools, we have managed to overcome these obstacles by teaching a wide range of visualization and supporting tools. Starting with GUI-based visualization tools and data analysis with Python, students put visualization knowledge into practice with increasing amounts of programming. At the end of the course, students can design and implement visualizations with D3 and other programming-based visualization tools. Throughout the course, we continuously collect student feedback and refine the teaching materials. This paper documents our teaching methods and considerations when designing the teaching materials.
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