We designed our lessons in Bootstrap:Data Science to be incredibly flexible, with options for teachers in multiple subjects from grade 612. Choose which of the following implementation models is right for you:
A Complete Data Science Class 1 semester to Full Year
Designed for Data Science teachers building an entire course! There are tons of projects, including Making an Infographic, Food Habits, Stress or Chill?, and Time Use, not to mention the Capstone Research Paper!
Our lessons can be broken up in distinct units, each with a clear theme.
Note: Many teachers pace themselves in order to have their students analyze additional datasets after completing all five units. Analyzing multiple datasets allows students to refine their skills and broaden and/or deepen domain knowledge. Most teacher start with one of the provided datasets (or a cleaned one they found themselves), and only have students collect their own data after working through their first analysis.
Unit 1: Who are Data Scientists, and what do they do?
Students see the wide range of people involved with mathematics, computing, and data science, and confront the challenge of answering messy questions with data. They explore a sample dataset, consider the relationship between probability and statistics, and learn the basic programming and statistics necessary to display that dataset using a variety of charts, plots and graphs.
Unit 2: Gathering, Analyzing, and Visualizing Data
Students choose a real dataset, or create their own! They explore this dataset, diving deep into the meaning, use, and interpretation of onedimensional analyses like histograms, boxplots, measures of center and spread. What do these tools tell us about our data, and when is it appropriate to use one tool over another?
Unit 3: Transforming and Playing with Data
Students learn to program functions, supercharging their programming arsenals with core algebraic concepts that allow them to create custom visualations that express many dimensions of data. They also learn how to sort, filter, and transform their dataset to search for patterns, zoom in on samples, and identify trends within subgroups of their samples.
Unit 4: Modeling the World Around Us with Data
In this unit, students apply their newfound programming power to identify relationships within their data, and developing linear (and even nonlinear!) models to describe those relationships. They generate numerous data displays, and combine them into a library of visualizations and inferences about their data.
Unit 5: Using Data Responsibly
As fullfledged data scientists, students consider the social impact of their work. How do we know that the tools we use to analyze data haven’t been tampered with? How do we know to trust the validity of our methods and datacollection? What are the ethical implications of this work? Using the visualization library from the previous unit, students conduct an original research project into their data. In doing so, they confront both analytical and ethical factors in their final report, and discuss the ethical standards that define a responsible data scientist.
Other Considerations
What Domain Knowledge do you care about? Do you want your students to focus on climate systems? Economics? Social Studies or History themes? Do you want them to design a survey for their school or neighborhood? What topics are important to your students? What topics are exciting to them? Your answers to these questions will determine the dataset(s) you’ll use or collect, which has significant impacts on engagement, relevance, and inclusion.
Which Math and Statistics learning goals do you have? The answer to this question will determine which lessons and projects from our library are relevant to you. A middleschool teacher might focus on lessons dealing pie and bar charts, histograms, etc. An Algebra teacher might focus on lessons about defining and composing functions. Meanwhile, a CS teacher might spend time on IfExpressions and conditionals.
More Analysis, Lots of Statistics Options 4 weeks, up to 1 semester
A module with programming aimed specifically at transforming tables and data visualation, designed for:

Statistics teachers

ModelingBased Science teachers

Computer Science teachers looking to teach more programming

Data Science teachers
This format includes multiple projectbased options, including Making an Infographic, Food Habits, Stress or Chill?, and Time Use.
…then choose what you need 
Other Considerations
What Domain Knowledge do you care about? If you’re integrating into a Science class, maybe you want students to study data from experiments, or data related to Earth Science or Biological phenomena from the Next Generation Science Standards. If you’re integrating into a Social Studies class, maybe you’re looking at datasets involving gerrymandering or redlinling. Your answer to this question will determine the dataset(s) you’ll use or collect, which has significant impacts on engagement, relevance, and inclusion.
Which Math and Statistics learning goals do you have? The answer to this question will determine which lessons and projects from our library are relevant to you. A middleschool teacher might focus on lessons dealing pie and bar charts, histograms, etc. An Algebra teacher might focus on lessons about defining and composing functions. Meanwhile, a CS teacher might spend time on IfExpressions and conditionals.
Charts, Plots, and Social Impact 1 to 4 weeks
A module with minimial programming, designed for:

Science teachers who want students to gather data and generate charts for lab reports

Math teachers who want students to experiment with charts and plots

History or Social Studies teachers who want students explore census data, voting data, economic data, etc.

Computer Science teachers who want a small, gentle exposure to Data Science for their students
In addition to whatever project you want your students to do with the data from your class, this format includes optional projects, such as Making an Infographic and Stress or Chill?.
Build a foundation… 
…then choose what you need 
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, and 1738598). Bootstrap by the Bootstrap Community is licensed under a Creative Commons 4.0 Unported License. This license does not grant permission to run training or professional development. Offering training or professional development with materials substantially derived from Bootstrap must be approved in writing by a Bootstrap Director. Permissions beyond the scope of this license, such as to run training, may be available by contacting contact@BootstrapWorld.org.