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2016 USA Elections: Data Visualizations

11/10/2016

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Image source: The Next Web
Data visualization is the graphical display of abstract information for two purposes:
sense-making (also called data analysis) and communication.
- Interaction Design Foundation

Enhancing Viewer Experiences in the 2016 USA Elections

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"Computer Science impacts every part of our lives."
In our class, we continuously strive to discover and uncover the impacts of Computer Science by making the most of the learning opportunities that surround us.

The following is a lesson on the 2016 Elections in reference to: Data Visualizations

Understanding the Purpose

At the start of class, I posted the following question in Google Classroom:
"What do you THINK is the PURPOSE of data visualizations?"

The following are some of the students' responses:
After reading each other's  responses, we synthesized our ideas into one PURPOSE statement:
​
"The purpose of data visualization is to transform large sets of data into viewer-friendly visuals (graphs, charts, etc...) that can be interpreted and understood by people to make informed decisions."

Artful Thinking: Looking 10 times 2

Note: I have been incorporating various Thinking Routines from Project Zero and the book "Making Thinking Visible" to structure our classroom discussions. These incredible routines have enriched the learning experiences in our classroom and have paved the way for deeper understandings.

Once we clarified the purpose of data visualization, we moved into an "Observing and Describing" routine called Looking: 10 times 2. I chose this routine because it "helps students slow down and make careful, detailed observations by encouraging them to push beyond first impressions and obvious features."

Initial Explorations
  1. Go to Google and search: "election results"
    1. Look at the visualization quietly for at least 30 seconds. Let your eyes wander.
    2. Make a list of 10 words or phrases based on what you SEE as you navigate that page.
    3. Repeat Steps 1 & 2: Look at the visualization again and try to add 10 more words or phrases to your list.
    4. Select 10 components and write what you THINK the PURPOSE was behind the choice of designers to visualize data in that manner.
  2. Click on this link from Fortune to gain a better understanding of the Google visualization tool.
  3. Click on this link from Politico. Share what is SIMILAR to the Google visualization tool and what is DIFFERENT.

​Students documented their learning and understanding in their Learning Guide. 
The slides below show samples of student thoughts.

Lesson Reflections

Reflecting Prompts:
  1. After our session on "2016 Election: Data Visualization", what NEW IDEAS do you have about data visualization?
  2. How did the routine "Looking: 10 times 2" affect your thinking about data visualizations?

Personalization of Information: Distorting Our Perceptions of Truth

In previous classes, we looked at how Google and Social Media create personalized experiences for their end-users. 
You might be able to relate to this scenario: you research a certain product on Google and the next thing you know, there are ads popping up in your news feed related to the product you just searched!

This article does an excellent job explaining how search engines personalize our "searches" based on:
our country, locality, personal history and social connections.

With this understanding, we began to wonder if many people were led to believe a certain outcome in the elections due to their personalized feeds. Because of the personalization of information, users essentially created a customized environment where only shared views and common perspectives were shown.

One student labeled this effect the "echo chamber", where we "shout out" our views and perspectives (on social media and search engines) and those (views and perspectives) are echoed back to us creating a "bubble of distorted truth".

On October 15, 2016, The Huffington Post published an article called: "How Facebook and Google's Algorithms Are Affecting Our Political Viewpoints". I will end this post in the same way they ended theirs with the following quote:
The Internet is showing us what it thinks we want to see,
but not necessarily what we need to see.
- Eli Pariser

Extra Resources:
  • Eli Pariser: Beware online "filter bubbles" (TED 2011)
  • D3.js: Bringing Data to Life using JavaScript

Share Your Thoughts

I hope these ideas and tips were meaningful to you .
Please comment and share your own experiences of exploring data visualizations.
I would love to hear your ideas so I can improve upon this process!
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