Data Visualization for Education

SDP Fellow Workshop January 2013

Jared Knowles
Policy Research Advisor, Wisconsin DPI

The Problem of Data Visualization

  • Data use is increasing rapidly within the education space
  • Policymakers are under increasing pressure to use data to inform decisions, justify funding, and guide practice
  • But, policymakers are often not statisticians, researchers, or quants
  • Data visualization is a way to bridge this gap
  • Proper data visualization will bring the data to the audience in a way they can understand quickly and use to inform decisions

Follow Along

What is dataviz?

Dataviz is...

  • An exploratory tool for understanding datasets
  • A communication tool for framing decisions and depicting problems
  • A way to showcase
  • A better way to present results of analyses

Dataviz is not...

  • Easy
  • A replacement for analysis
  • Infographics
  • Easy!

Data visualization is a tool for communicating a specific feature of a datset in an approachable and efficient manner

If a picture is worth a thousand words, a good data visualization must always be better than a table.

Student Growth

Objectives

  1. Review data visualization principles and chart types
  2. Look at applications in education data from an SEA
  3. Challenges with administrative data and policymaking
  4. Best practices and advice
  5. What tools to use
  6. Activity!

Example

How can we improve this simple scatterplot?

plot of chunk plot

Principles

  • Elements of a chart
  • Chart Types and Data Types
  • Dimensionality
  • Scale
  • Complexity
  • Technical details
  • Beyond charts

plot of chunk plot1

Chart Elements

There are a few things that all charts need. There are sometimes strong cases to deviate from these, but they are good rules of thumb.

  • Axis labels and a title
    • These make the chart self-explanatory
  • A legend
    • What is the unit in the graphic?
  • A scale
    • How are units mapped to the visual space
  • Annotations
    • Author and data source (depending on distribution)

Dimensions

  • Charts and data are made up of dimensions (e.g. a bar chart is x and y)
  • Additional dimensions can be represented by additional aesthetics or chart elements (e.g. color, size, shape, etc.)
  • Dimensions can also be shown by multiple plots (e.g. a filmstrip)
  • Smart use of dimensions allows us to increase the information density of our charts

plot of chunk unnamed-chunk-2

How you turn dimensions in the data into visual cues for your audience is everything.

Reviewing Chart Types

Stacked Bar

Box and Whisker

Bullet Chart

Calendar