Day 10: Data Visualization

Learning Objectives

• DAT-2.D: Extract information from data using a program.

Essential Questions

• How can data visualization help reveal patterns and insights?
• What types of visualizations are appropriate for different kinds of data?
• How do we create effective and honest visualizations?

Materials Needed

• Presentation slides on data visualization principles
• Sample datasets for visualization
• Visualization tools (spreadsheets, programming libraries, or online tools)
• Computers with visualization software
• Visualization evaluation rubric

Vocabulary

• Data visualization
• Chart
• Graph
• Infographic
• Bar chart
• Line graph
• Scatter plot
• Histogram
• Pie chart
• Misleading visualization

Procedure (50 minutes)

Opening (8 minutes)

1. Review and Connection (3 minutes)

   • Review data processing from previous lesson
   • Connect to today's focus on visualizing data

2. Warm-up Activity (5 minutes)

   • Show students two different visualizations of the same data
   • Ask: "Which visualization communicates the information more effectively? Why?"
   • Discuss how visualization choices affect data interpretation

Main Activities (32 minutes)

3. Lecture: Principles of Effective Data Visualization (12 minutes)

   • Explain why visualization is powerful for understanding data:
     • Humans process visual information efficiently
     • Patterns are easier to spot visually than in raw numbers
     • Complex relationships can be communicated quickly
   • Discuss key principles of effective visualization:
     • Choose the right visualization type for the data
     • Maintain appropriate scale and proportion
     • Use clear labels and legends
     • Minimize chart junk and decoration
     • Be honest with the data (don't distort)
   • Introduce common visualization types and their uses:
     • Bar charts: comparing categories
     • Line graphs: showing trends over time
     • Scatter plots: showing relationships between variables
     • Histograms: showing distributions
     • Pie charts: showing proportions of a whole
   • Show examples of both effective and misleading visualizations

4. Demo: Different Visualization Techniques for Different Data Types (8 minutes)

   • Demonstrate creating various visualizations using available tools
   • Show how the same data can be visualized in different ways
   • Explain how to choose appropriate visualizations based on:
     • The type of data (categorical, numerical, time series)
     • The question being answered
     • The audience's needs
   • Demonstrate how to customize visualizations for clarity

5. Activity: Create Visualizations from a Dataset (12 minutes)

   • Students work individually or in pairs
   • Provide a dataset with multiple variables
   • Students create at least three different visualizations that:
     • Answer different questions about the data
     • Use appropriate visualization types
     • Follow principles of effective visualization
     • Reveal patterns or insights in the data
   • Students document the insights gained from each visualization

Closing (10 minutes)

6. Visualization Gallery Walk (5 minutes)

   • Students post or share their visualizations
   • Class circulates to view and provide feedback
   • Identify particularly effective visualizations and insights

7. Assessment and Preview (5 minutes)

   • Students submit their visualizations with explanations
   • Preview that next class will focus on metadata

Assessment

• Formative: Quality of visualization creation during activity
• Visualization Submission: Appropriateness of visualization types, clarity of presentation, and quality of insights

Differentiation

For Advanced Students

• Create more complex visualizations (interactive, multi-variable)
• Explore advanced visualization types (heat maps, network graphs)
• Analyze how to optimize visualizations for specific audiences

For Struggling Students

• Provide templates for basic visualization types
• Offer step-by-step guides for creating visualizations
• Focus on simpler datasets with clearer patterns

Homework/Extension

• Find an example of a misleading visualization and explain how it distorts the data
• Create a visualization of a personal dataset (fitness data, spending habits, etc.)
• Research how data visualization is used in a field of interest

Teacher Notes

• Have examples ready of both effective and misleading visualizations
• Make connections to how visualizations are used in media and research
• Emphasize the ethical responsibility to represent data honestly
• Consider discussing accessibility in visualization (colorblind-friendly palettes, etc.)
• This concludes Week 2 of the unit