Concept E1.4
Media Literacy & Digital Citizenship

Graphical literacy

Comfortably read graphs with accuracy and make sense of data visualizations by answering questions about how the data is represented with precision.

K–2 Competencies

Answer questions about whole number numerical data or categorical data represented visually (e.g., bar graphs, picture graphs).

K-2.E.1.4a

Recognize how data is organized into categories or groups. e.g., each bar or picture represents a certain quantity in a graph

K-2.E.1.4b

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

Answer questions about fractional valued numerical data or categorical data represented visually with one or two variables.

3-5.E.1.4a

Recognize unusual data points and consider reasons why they might appear.

3-5.E.1.4b

Work with a variety of data types, including numerical data, charts, graphs, and visual representations to draw conclusions and understand the story the data is telling.

3-5.E.1.4c

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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

Answer questions about continuous numerical scaled data, location data, and/or categorical data represented visually with multiple variables.

6-8.E.1.4a

Describe the relationships (or lack thereof) represented in scatterplots (e.g., direct vs. inverse, positive vs. negative).

6-8.E.1.4b

Review non-standard data representations that appear in popular media, identify the key visual elements and what they mean, and describe the intent and evaluate whether or not it is successful.

6-8.E.1.4c

Classroom resources

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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

Answer questions about and explain the data in a variety of data visualizations, including non-standard visualizations. Extract key insights, trends, and patterns from the data.

9-10.E.1.4a

Describe the potential relationships (or lack thereof) represented in scatterplots (including linear, exponential, and logarithmic) and debate which function is the best representation for the shape and context.

9-10.E.1.4b

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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

Understand how uncertainty around point and effect estimates are communicated on data visualizations with error bars.

11-12.E.1.4a

Evaluate the effectiveness of data visualizations, including the risk of misleading the reader.

11-12.E.1.4b

Classroom resources

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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

Describe the potential relationships (or lack thereof) represented in scatterplots (including linear, exponential, logarithmic, polynomial, and piecewise) and debate which function is the best representation for the shape and context.

Advanced E1.4a

Visualize confidence intervals or margins of error using error bars with computer-based software.

Advanced E1.4b

Visualize margins of error of a continuous variable using error bands with a computer-based software.

Advanced E1.4c

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