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Tune in to the Data Games on April 16th!
YDSQ Bootcamp: Week 4
YDSQ Bootcamp: Week 4
Welcome to Week 4 of Boot Camp! This week is all about discovering knowledge with data. You'll discover how authentic questions from student voices can create greater value in your own data discoveries.
Lesson: Discovering Knowledge with Data
Lesson: Discovering Knowledge with Data
Hey teachers! Check out this facilitator guide before you walk through this lesson with your students. It provides step by step instructions to help you set up the group activity.
If you are a student going through the lesson on your own, you can also read through this guide and do your own version of the activity!
Part 1: Introduction to Data Modeling
Recall in the Week 1 Lab you were introduced to the Data Science Lifecycle.
Over the last few weeks, you have been learning about asking questions, data creation, and data collection.
Today we will be focusing on Data Modeling.
Data modeling is about extracting meaning from data. Data re-modeling is about making updates to an existing data model. You will likely go through many iterations of data modeling and remodeling in your data science journey!
You got the chance to start finding your own insights from data in Week 3 and this week you will be getting even more hands-on experience.
Part 2: How to Make Your Own Visuals
In the embedded report from Week 3 there was a page that showed Net Worth by Gender.
Watch the video to the right to see how you could make some changes to that visual to explore new insights!
Part 3: Mini Project!
Now it's your turn to try out making your own visuals to explore!
Start by getting a copy of the report from your facilitator, or you will walk through the steps as a class to create your own copy: YDSL Week 4 Activity Guide
Follow the instructions in the first 6 pages of the report
Alter the visuals in the rest of the report pages or build your own from scratch!
Part 4: Reflect
Discuss as a Class!
What findings did you discover in the time that you've explored?
In what scenarios could you draw a conclusion? In what scenarios could you not?
What additional questions does this raise for you?
What additional sources of data would you explore if you had time?
Part 5: Sample Size
Watch this video to learn about being careful making conclusions from small sample sizes!
Part 6: Key Takeaways
Your voice as a student and the authentic questions that you are passionate about are what will take any analysis from insightful to impactful.
Building visuals is fun :) Answering questions normally leads to even more questions. There are many avenues you can explore with the same data set.
Sample size is important! You need to make sure you have enough data to be able to draw meaningful conclusions.
Lab: Data Modeling—Part I
Lab: Data Modeling—Part I
Work in groups or individually to work through the lab below!
https://colab.research.google.com/drive/1jeKZU6aDbVTwzs4va1oe2CFCp7MR5Wzp?usp=sharing
Data Games Prep: Authentic Problems & Data Questions
Data Games Prep: Authentic Problems & Data Questions
It's already Week 4 and you've learned so much! Let's start with a recap of some of those great topics:
You've learned about data visualizations and how to build them
You've narrowed down your Data Games story project topic to one
You've collected some data sources for your topic
You've learned about data features (like height, favorite show, etc.) in a data set
You've thought about relationships between data sets
The data science skills you have been learning will be a big part of your Story-Project in the Data Games, but equally as important will be the soft skills and storytelling abilities you practice.
Watch this video to learn about some of the qualities you should be keeping in mind throughout your experience.
Authentic Questions
Student Voice
Collaboration
Expertise
Watch this video of Greta Thunberg (from 2:08 - 5:08) who gave this talk at 15 years old on a topic that is important to her.
How did Greta's talk incorporate the qualities listed above?
Take a moment to discuss as a group.
This week, we want you to Channel Your Inner Greta!
Answer these questions as a group and send your answers to your mentors to get their input!
Who is your audience? Who are you trying to impact or reach with your project? Who might take an action based on the insights?
What are some Authentic Problems that you care about associated with your chosen topic? (see example below)
What are some Data Questions that could help you address one or more of your Authentic Problems?
Refer to your Mini Project from Part 4 this week and the features in the data sets you've collected to help create Data Questions
Here's An Example
Topic: Climate Change Education
Audience: School boards - could take action on school or district policy
Authentic Problem: Climate Change Education is not widespread in the U.S., most students are unaware
Features in Data Sets: Number of schools, teachers, and students involved in climate change education; Where in the U.S. climate change education is (and is not) happening. Impact on students of existing climate change education.
Data Questions: Has the number of schools teaching climate change changed over the past 30 years? Has the number of students receiving climate change education changed over the past 30 years? What impact has existing education had on students' awareness of and concern over climate change?
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