Concept E1.5
Media Literacy & Digital Citizenship

Representational fluency

Identify how layout (ordering, scale, and axes) choices increase clarity or potentially mislead an audience.

K–2 Competencies

Compare and/or contrast different representations of the same data, including physical models (e.g., block towers), bar graphs, and picture graphs, and describe how they differ.

K-2.E.1.5a

Use visual cues to interpret data. e.g., bar graph, taller bars mean higher frequency

K-2.E.1.5b

Classroom resources

Classroom Tip
Getting Started

Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

3–5 Competencies

Compare and/or contrast various visualizations of the same data by altering different features (e.g., reordering bars, changing colors), and explain how these changes affect what is highlighted or obscured in each representation. e.g., bar graph sorted by size highlights the most popular option, while sorting alphabetically can make comparison challenging

3-5.E.1.5a

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Getting Started
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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

6–8 Competencies

Compare and/or contrast various representations of data sets with multiple features and describe what is emphasized, de-emphasized, or obscured in each representation.

6-8.E.1.5a

Describe how different ways of representing data can improve clarity or mislead.

6-8.E.1.5b

Classroom resources

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Getting Started
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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

9–10 Competencies

Compare and/or contrast visualizations of the same numerical data at different scales and understand how the scale affects people's interpretation. e.g., accurately representing the relative magnitudes vs. exaggerating them

9-10.E.1.5a

Critique misleading visualizations, such as those with truncated axes, cherry-picked data points, confusing colors, or manipulated scales. e.g., graph starting at 50 (not 0) can make a 5% drop look like a crash

9-10.E.1.5b

Classroom resources

Classroom Tip
Getting Started
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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

11–12 Competencies

Compare and/or contrast various representations of relative frequencies and proportions, identify elements of each representation that facilitate or hinder the identification of relative proportions, and explain the reasoning behind conventions. e.g., ordered or unordered stacked bar graph

11-12.E.1.5a

Compare and/or contrast various ways to represent distributions and their measures of center (e.g., histograms, density plots, box plots) by plotting two distributions on the same graph and explaining how different representations facilitate or hinder the visibility of differences and associations.

11-12.E.1.5b

Classroom resources

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Getting Started
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Data Science Starter Kit Module 5: Telling the Story - Visualization and Communication

Welcome to the culminating skill of data science—communicating your findings effectively so others can understand and act on them! This module focuses on how to create clear visualizations and compelling narratives that make data accessible and meaningful to different audiences.🔗

Visualization and Communication isn’t about creating fancy graphics or impressive presentations. It’s about developing the empathy and clarity to think, “How can I help others understand what this data means and why it matters to them?” The best data science in the world is useless if it can’t be understood and applied by the people who need it.

Advanced Competencies

Compare and/or contrast 2D and 3D bar graphs and pie charges and identify how unnecessary use of three dimensions obfuscates the relative frequencies and/or proportions of the data.

Advanced E1.5a

Compare and/or contrast varying bin sizes to demonstrate how different degrees of granularity in a histogram or other visualization type can lead to different interpretations.

Advanced E1.5b

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