Lesson Series: Using Google Sheets to Create Visualizations of Attitudinal Data

Objective: Students will learn to analyze and visualize attitudinal data using Google Sheets, following the Data Science Process to produce meaningful insights and visualizations.

Lesson 1: Framing Questions and Exploring the Dataset

Goal: Understand the role of attitudinal data in research and formulate questions that guide analysis.

1. Warm-Up (10 minutes):

   • Discuss examples of attitudinal data (e.g., surveys, opinion polls).

   • Ask: "Why is it important to visualize this type of data?"

2. Activity: Reviewing Available Datasets (20 minutes):

   • Provide students with a list of available datasets (e.g., Pew Research, other attitudinal datasets).

   • Students browse datasets to identify one that aligns with their project topic.

   • Discuss: "What makes a dataset relevant to your project?"

3. Activity: Asking Questions (20 minutes):
   
   

   • Provide students with a Pew dataset overview (structure, types of variables).

   • Students write down:

     • "What questions am I trying to ask the data?"

     • "What questions can I ask this dataset?"

   • Pair-share responses and discuss as a class.

4. Homework (Optional):
   
   

   • Research potential additional questions related to their topic.

Goal: Understand the role of attitudinal data in research and formulate questions that guide analysis.

1. Warm-Up (10 minutes):
   
   

   • Discuss examples of attitudinal data (e.g., surveys, opinion polls).

   • Ask: "Why is it important to visualize this type of data?"

2. Activity: Asking Questions (20 minutes):
   
   

   • Provide students with a Pew dataset overview (structure, types of variables).

   • Students write down:

     • "What questions am I trying to ask the data?"

     • "What questions can I ask this dataset?"

   • Pair-share responses and discuss as a class.

3. Homework (Optional):
   
   

   • Research potential additional questions related to their topic.

Lesson 2: Gathering and Organizing Data

Goal: Learn to clean and prepare datasets for analysis.

1. Introduction (10 minutes):
   
   

   • Demonstrate how to download and open the dataset in Google Sheets.

   • Explain common cleaning tasks: removing duplicates, handling missing values, and standardizing formats.

2. Activity: Cleaning Data (30 minutes):
   
   

   • Students:

     • Remove irrelevant columns.

     • Filter data to focus on their research question.

     • Normalize data formats.

   • Explore basic Google Sheets functions for cleaning (e.g., =TRIM, =CLEAN).

3. Extension (Optional):
   
   

   • Introduce pivot tables for summarizing data.

Lesson 3: Model

Goal: Understand the types of charts and graphs available in Google Sheets and their use cases.

1. Warm-Up (10 minutes):
   
   

   • Show examples of visualizations (scatter plots, line charts, pie charts, bar graphs).

   • Ask: "What story does this chart tell?"

2. Activity: Exploring Features (30 minutes):
   
   

   • Students:

     • Use sample data to create different types of charts.

     • Experiment with formatting options (titles, axis labels, colors).

   • Discuss how each chart type represents data differently.

3. Reflection (10 minutes):
   
   

   • Ask: "Which chart types best represent the kind of data I’m working with?"

Lesson 4: Creating Visualizations

Goal: Develop meaningful visualizations for their dataset.

1. Warm-Up (5 minutes):
   
   

   • Recap visualization basics and best practices.

2. Activity: Building Visualizations (40 minutes):
   
   

   • Students:

     • Choose relevant chart types based on their research question.

     • Create at least 3 visualizations using Google Sheets.

     • Apply formatting to enhance readability and communication.

3. Pair Review (10 minutes):
   
   

   • Students share their visualizations with a partner and receive feedback.

Lesson 5: Analyzing and Communicating Insights

Goal: Critically evaluate visualizations and communicate findings.

1. Activity: Analysis (30 minutes):
   
   

   • Students write concise descriptions of their visualizations, addressing:

     • What does this chart show?

     • What are its strengths and weaknesses?

     • How effectively does it communicate the data?

2. Discussion: Choosing Final Visualizations (20 minutes):
   
   

   • Students select 2-3 visualizations they feel best represent their dataset.

   • Write a brief justification for their choices.

Lesson 6: Presenting Findings

Goal: Share insights and reflect on the visualization process.

1. Preparation (20 minutes):
   
   

   • Students prepare a short presentation or write-up that includes:

     • Their research questions.

     • Visualizations.

     • Key insights and reflections.

2. Presentations (30 minutes):
   
   

   • Students present to the class or in small groups.

   • Encourage peer feedback and discussion.

Extensions

• Compare Google Sheets visualizations with those created in Tableau or Datawrapper.

• Explore interactivity by embedding visualizations into web-based reports or student portfolios.

• Analyze additional datasets to build confidence and transfer skills.

Let me know if you'd like further refinement or additional activities!

The first part. Add a piece that has students review available datasets (PEW, etc) for datasets that likely align with their projects.