Teacher Resources for Data Science

Implementation Options [link] Bootstrap:Data Science was designed to be flexible, allowing for implementations in Middle and High School ranging from 1-week exposures to full-year courses! Find recommendations for the course structure that’s right for you.

Online Community [Discourse] - Talk with other Bootstrap teachers, ask questions, and share ideas!

Remote Instruction [link] - specific recommendations for in-person v. remote instruction.

Poster Set for Classroom Walls [link] - This poster set features Pioneers in Computing and Mathematics. For greater impact, engage your students with these materials using our Computing Needs All Voices lesson. (You can also purchase a printed set yourself!)

Make an Infographic : Infographics are a powerful tool for communicating information, especially when made by people who understand how to connect visuals to data in meaningful ways. This project is an opportunity for students to become more flexible math thinkers while tapping into their creativity. This project supports the learning goals of our lesson on Bar and Pie Charts.

Design a Survey : Students come up with a research question and design a survey to gather data to answer it. They exchange surveys to get some hands-on practice with clean and dirty data and incorporate what they learn to polish their surveys. This project supports the learning goals of our lesson on Data Collection.

Snack Habits : Students analyze their class' snacking habits in comparison with data on childhood obesity in the U.S. This project supports the learning goals of our lesson on The Data Cycle.

Time Use : Students investigate the amount of time they spend interacting with technology and doing homework as compared with other Americans.

Research Capstone : This project can be used as a capstone for Bootstrap: Data Science. It is designed to give students a deep dive into a dataset and use everything they’ve learned throughout the course, not only about making and interpreting visualizations, but about the practice of refining our questions through the Data Cycle and deciding which visualizations are most useful in telling the data’s story. This project is an extension of the Project: Dataset Exploration.

Dataset Exploration : Students choose a real world dataset that is interesting to them and practice making and interpreting a range of visualizations using that dataset. This project spans up to nine of our Data Science lessons, each of which includes an optional section with project-specific directions. We have built a Library of Datasets to support this project.

When Data Science Goes Bad : Students investigate four types of threats to validity by pretending to be “bad data scientists” who fail to consider the impact of selection bias, bias in the study design, poor choice of summary data, and confounding variables. This project supports the learning goals of our lesson on Threats to Validity.

Contracts [link] - A PDF of the contracts pages from the back of the student workbook.

Glossary [link] - All of the vocabulary words (and their definitions) used in this pathway.

Bilingual Glossary of Bootstrap Terms (English-Spanish) [PDF] - For teachers with ELL/ESL students, we provide a bilingual glossary for all of the terms used across our curriculum library.

Blank Data Cycle Worksheet - [html] - When students need scaffolding for answering a question with data.

Collection of Bootstrap:Data Science Desmos Activities [link] - All of our Desmos Data Science lessons, in one place.

Sentence Starters [html] - Use these sentence starters to help students describe patterns, make predictions, find comparisons, share discoveries, formulate hypotheses, and ask questions.