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HOW TO CULTIVATE
CRITICAL THINKING
THROUGH VISUALIZATION
Seeing beyond the graph:
Fanny Chevalier
Assistant professor
University of Toronto
Winnpeg Sun, 2013The West Morland Gazette, 2015unknown university board
Map source: www.npr.org
Image source: REUTERS/Carlos Barria
Source: John Muyskens,Washington post, October 2016
Source: John Muyskens,Washington post, October 2016
How well do we understand data that we see everyday?
Relate: Using concrete scales to communicate complex measures
How well do we understand data this represented visually?
Educate:Visualization literacy at elementary school
How well can we communicate data visually?
Engage:Visualization literacy at elementary school
1.
2.
3.
How well do we understand
the data that we see everyday?
1.
350 ml 475 ml 500 ml
39g of sugar 52g of sugar 65g of sugar
Recommended daily intake: 25g
(World Health Organization)
PRESENTATIONS
350 ml 475 ml 500 ml
39g of sugar 52g of sugar 65g of sugar
Recommended daily intake: 25g
(World Health Organization)
Image source: REUTERS/Shannon Stapleton
Video source: http://www.debtclock.ca/
USD$20.7 trillion
USD$ 20,760,852,675,267
USD$515 billion
CAD$ 650,881,545,273
USD$ 512,237,267,314
Retrieved on Feb.26, 10:45AM EST from: http://www.usdebtclock.org/ and http://www.debtclock.ca/
A concrete scale is a visualization
that conveys a complex measure by re-expressing it
using familiar objects from the real world
20 trillions of dollars59g of sugar
Using Concrete Scales:A Framework forVisual Depiction of Complex Measures
Chevalier, Vuillemot & Gali. IEEETVCG / Infovis 2013
COGNITIVE MECHANISMS
Anchor and
adjustment
Unitization
Analogy
0 measure
0 measure
0 measure
Using Concrete Scales:A Framework forVisual Depiction of Complex Measures
Chevalier, Vuillemot & Gali. IEEETVCG / Infovis 2013
How well do we understand
the data that we see everyday?
1.
Some measures may be difficult to grasp.
Relate data to more familiar concepts can help.
How well do we understand
data that is represented visually?
2.
Misleading visual representations
Perceptual biases
Image source:
NPR visual team.
VISUALIZATION LITERACY
ability to extract information from visualizations
and think critically about it
ability to communicated data in a visual form
as truthfully as possible
Where and when
do we learn these skills?
Qualitative coding of
textbook visual material
C’est la vis:Visualization Literacy at Elementary School
Alper, Henry Riche, Chevalier, Boy & Sezgin.ACM CHI 2017.
We encoded 2600 visual representations in
5000 textbook pages
C’est la vis:Visualization Literacy at Elementary School
Alper, Henry Riche, Chevalier, Boy & Sezgin.ACM CHI 2017.
Degree of Abstraction
Scott McCloud,
Understanding Comics
Degree of Abstraction
Scott McCloud,
Understanding Comics
C’est la vis:Visualization Literacy at Elementary School
Alper, Henry Riche, Chevalier, Boy & Sezgin.ACM CHI 2017.
C’est la vis:Visualization Literacy at Elementary School
Alper, Henry Riche, Chevalier, Boy & Sezgin.ACM CHI 2017.
Same data, different abstraction levels
C’est la vis:Visualization Literacy at Elementary School
Alper, Henry Riche, Chevalier, Boy & Sezgin.ACM CHI 2017.
Interested and focused
for 30 minutes
Disrupted class dynamics
Interacted a lot
Completed all activities
Peer learning
Verbalization
Retention
How well do we understand
data that is represented visually?
2.
Decoding and understanding visualizations is a
complex activity that requires knowledge and skill.
Visualization education can help.
How well can we communicate
data visually?
3.
VISUALIZATION LITERACY
ability to extract information from visualizations
and think critically about it
ability to communicated data in a visual form
as truthfully as possible
http://coloringclimate.com/
Color where carbon emissions from fossil fuels are the
greatest, which looks similar to a population density
map since this type of greenhouse gas is caused by
human activity.
http://coloringclimate.com/
See if you can color 20 football fields in under a
minute, which is about how fast we have been losing
global forests for the past 25 years
http://www.dear-data.com/
http://www.dear-data.com/
DataInk: Creative and Direct Data-Oriented Drawing
Xia, Riche, Chevalier, De Araujo,Wigdor.ACM CHI 2018 [Honourable mention]
DataInk: Creative and Direct Data-Oriented Drawing
Xia, Riche, Chevalier, De Araujo,Wigdor.ACM CHI 2018. [Honourable mention]
How well can we communicate
data visually?
3.
There are many challenges.
By reconciling creative drawing and data binding
we can engage people with data.
–Alberto Cairo
“[data is] always noisy, dirty, and uncertain.”
–Fanny Chevalier
“… and so is the way
we portray and perceive it.”
Relate
Educate
Engage
1.
2.
3. http://fannychevalier.net
TorCHI.org World Usability Day 2018 - Talk by Prof. Fanny Chevalier

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TorCHI.org World Usability Day 2018 - Talk by Prof. Fanny Chevalier