Resources and Methods in Assessment Data Visualization

Content originally presented by Courtney Vengrin, Ph.D., Director of Curricular Assessment and Teaching Support, Assistant Teaching Professor, Iowa State University – College of Veterinary Medicine

A picture is worth a thousand words, but when it comes to data visualization, how do you make that picture?

在评估的世界里,我们经常被数据淹没. 通常,这些数据只对少数经常使用这些数据的人有意义. Through data visualization, 你可以把你的关键数据的故事讲给更广泛的受众——无论是教员, students, stakeholders, or accrediting bodies.

Why Visuals?

Visuals matter. For most of us, we are able-bodied sighted individuals. We process most of our information every day in a visual manner. If you think about driving, most signs are visuals. It speeds up our process time and overcomes language barriers, and is used to communicate quickly and clearly what is important.

研究还表明,数据可视化在机构设置中很重要. A study by Azzam in 2013 found that:

“数据可视化的使用可以提供一种更好的方式来传达对学生成功的影响.”

可视化还可以帮助我们的学生评估和监控自己的学习.

Benefits of Connecting Visuals to Assessment Data

那么我们如何利用这种强大的讲故事的方法,并将其与我们的交流联系起来 assessment processes and overall narratives? 数据可视化是一种让人们关心数据和讲述学生故事的好方法, teaching in the programs and learning. As an assessment professional, 你可以把你的一排排数据转化成对那些不会说评估语言的人来说有意义的东西. 你可以很容易地证明并清楚地传达我们的项目正在产生影响, and our students are finding success.

What is Assessment Data Visualization?

首先,让我们回顾一下数据可视化的定义. Data visualization is combining the data gathered from an evidence-based practice, whether teaching or programs, with a visual to tell a larger impactful story, whether of the class, improved learning over a program, or whatever you need to communicate to a broader audience. 这是一种非常有效的方式,可以将电子表格中的信息传递给那些可能没有参与这个项目的公众.

 

5 Questions to Ask Before Visualizing Data

This isn’t creating any old chart. 这是一个精细的过程,专注于对故事至关重要的数据和真正重要的东西. It leaves no data behind and allows us to focus on the main point. 在我们开始进行数据可视化之前,有5个问题需要问自己.

  1. What data do you have?

    首先考虑你需要什么样的数据来构建你想要传达的信息. Examples could include quantitative and qualitative data; including student scores, predictor exams, survey data and other metrics from employer and alumni surveys. Comment sections and timelines can also create good visuals. 当你收集数据时,问问自己——是否还有更多的分析要做?

  2. Is your data ready for visualization?

    Are your pieces of data just numbers on a spreadsheet, or do they need to be analyzed to come alive, have meaning, and start telling a story? 作为评估专家,您很可能已经做了一些这样的分析. Do you need to do additional statistics on this data? 问问自己,什么会对整个故事产生最大的影响,然后开始集思广益. Do percentages or mean scores work better than plain data?  Are there any ranges that will help illustrate your main point? Any pull quotes or pictures that will tell a better story?

  3. What are the key points of your message?

    When you are working on the specific message of the story, think through why you have been tasked with creating this visual. Is it for accreditation purposes? Did the Dean ask you to create an annual report? Keep in mind the key points to drive home your overall story, 如果这些关键点回答了你最初要解释的问题. 注意,你也不必在可视化上走极端. Your objective is clarity over quantity. Also, 考虑从外部角度来看你目前所构建的内容,看看你的数据是否符合你的关键点和整体故事.

  4. What important facts often get overlooked?

    As an assessment professional, you know your data very well. 你很可能对在演示和最终报告中可能被忽视的内容有很好的洞察力, 或者你的信息没有有效地传达到关键点上. 我们不希望潜在的观众用事实和支持数据玩“沃尔多在哪里”的游戏. 如果有任何模糊或令人困惑的地方,考虑添加视觉效果来帮助澄清.

  5. What does a good visual look like?

    在回答了前四个问题并弄清楚你要传达的信息之后, what the key points are to support that message, 以及在这种叙述中可能被忽视的东西, you are armed and ready to start creating your first visual. 当你开始时,这里有一些有用的设计原则来制作一个引人注目和有效的视觉效果.

DIETER RAMS PRINCIPLES OF DESIGN (MODIFIED FOR DATA)

这些原则是由Dieter Rams起草的,并被广泛接受为视觉设计的良好基础. that are modified for data visualization,

GOOD DATA VISUALIZATION IS:

  • Innovative, modern and current
  • Making data useful
  • Aesthetic pleasing to view
  • Making data understandable
  • 不引人注目或分散-作为一个麦克风,而不是一个扩音器为您的数据
  • 诚实-不要改变轴或改变视觉来动摇或扭曲你的分析和观点
  • Long-lasting and stands the test of time
  • 彻底到最后的细节-图形的每个方面都是经过考虑和有意的
  • Economically friendly – how can you make these visuals easy to create?
  • Simple and involves as little design as possible – less is more

 

In Conclusion

数据可视化提供了一种以不同方式查看数据的方法,并为我们提供了更好的机会来检测模糊的模式和联系. 视觉效果是你工具箱中的一个强大工具,可以帮助你的听众更好地理解你在你的机构所做的良好评估工作.

***

有关此主题的更详细信息,包括一些逐步示例,请观看 Resources and Methods in Assessment Data Visualization webinar recording.

***


Courtney Vengrin, Ph.D.

Dr. 考特尼·文格林(Courtney Vengrin)是兽医学院课程评估和教学支持主任, 兽医临床学系助理教学教授. 然而,她很快指出,她内心深处是一个社会科学家和数据书呆子. Dr. Vengrin has an M.S. degree in Agricultural Extension Education and a Ph.D. 农业、领导力和社区教育,都来自弗吉尼亚理工大学. 她喜欢说自己是一名“正在康复”的高中教师,并试图应对她在10年前的今年开始了自己的教育生涯的事实. Dr. Vengrin的研究兴趣包括评估和评估文化, technology-enhanced educational practices, and student success in the college environment. 她对数据科学和数据可视化充满热情,喜欢参与有关统计的对话!

 


 

希望了解Weave如何帮助您简化评估流程?

Fill out the form below for a personalized demo. You’ll receive advice on your current accreditation system, as well as an overview of how Weave can simplify your workflows, 改进协作,使您的评估和fun88乐天使过程取得成功.



Leave your comment