Teaching Data Visualization
Gabrielle Annala gannala@luc.edu
Sarah Morris smorris4@luc.edu
The ALA Big Six information literacy standards emphasize the importance of identifying and
fulfilling information needs. Often these information needs are met with a basic library
instruction session. But, creating something new and communicating ideas to an audience
is also an important step in this process. According to the Big Six, these frequently
overlooked steps are known as the synthesis and evaluation stages.
CLASSROOM
All students are working with
the same assignment/data and
have to meet a specific set of
criteria to complete
assignment objectives.
A modern trend in information science is data visualization which empowers students to
create and communicate their new accumulation of knowledge. During this session we will
outline class objectives, learning outcomes, lesson plans, and activity ideas for incorporating
data visualization into an embedded classroom experience or workshop style seminar.
These classroom experiences are designed to expose students to new tools and to act as a
bridge between information literacy stages, such as finding information and synthesizing that
information into a new idea. Data visualization encourages students to contextualize their
projects and often brings about a new perspective, demonstrating intellectual growth. This
type of outcomes-oriented instruction is aimed at giving students the tools to not only
understand the concept, but deliver a final product.
Objectives
& Outcomes
Based on ACRL definition of an
information literate individual,
five criteria for objectives and
outcomes were defined. The
overarching goals of the
instructional sessions are to
empower students with new
ways of communication and
introduce them to new tools.
Students should be able to
think critically about visual
representation of information.
Access
Evaluation
Initial Questions:
What do you want to know?
Where can we find it?
Students will be able to
identify, locate, and use tools
to visually represent
information.
Initial Questions:
What is useful?
Do we have new questions?
Students will recognize and
employ criteria to evaluate
data visualizations
Teaching Methods
WORKSHOP
Students are exposed to new
ideas and have the tools and
inspiration to get started on
future projects
Analysis
Initial Questions:
What questions have we
answered?
What do we now know?
Students will recognize and
employ criteria to evaluate
data visualizations
GENERAL OUTCOMES
Build a foundational
awareness of data
visualization tools and
techniques with a
discussion component
for practical application
Synthesis
Initial Questions:
What new knowledge have
we created?
Students will differentiate among
different types of data
visualizations and will select
visualizations that suits their
information needs
Tools Used
Active Learning Techniques - Provided sample datasets for
in class creation, compare/contrast good and bad
examples
CLASSROOM
WORKSHOPS
• Evaluative Exercise - Look at the
same data represented in different
ways
• Branding Awareness - Identifying
Visual cues for continuity
• Value added content - Empty
workflows, symbols, and
representations to create value not
fill space
• Share and demo resources and
tools
• Group work activity: design a
visualization for a data set
• In-class discussion
The Final Product
Students are able to create a content deliverable to both professor and client. All stages
of knowledge growth from access to creation are included and completed independently.
Students are exposed to new ideas and have the tools and inspiration to get started on
future projects.
Creation
Initial Questions:
How do we tell the story?
What tools do we need?
What adds value?
Students will create data
visualizations in order to
communicate ideas