These materials are designed for Algebra 2 teachers looking to add a project-based approach to their existing practice. In a few class periods, students will have learned all of the programming they need to explore quadratic, exponential, and logarithmic relationships in data (periodic models coming this fall!).

These were initially developed thanks to a NSF grant, in partnership with Educational Development Center and Massachusetts Department of Elementary and Secondary Education.

Lesson Plans

Introduction to Data Science

Students learn about Categorical and Quantitative data, are introduced to Tables by way of the Animals Dataset, and consider what questions can and cannot be answered with available data.

Simple Data Types

Students begin to program, exploring how Numbers, Strings, Booleans and operations on those data types work in a programming language. Booleans offer an excellent opportunity for students to explore the meaning and real-world uses of inequalities.

Contracts: Making Tables and Displays

Students learn about functions for sorting and counting data in tables, then are introduced to one-variable displays.

Exploring Linear Models

Students use linear models to investigate relationships in demographic data about US states using an inquiry-based approach, involving hypothesizing, experimental and computational modeling, and sense-making.

Exploring Quadratic Models

Students investigate quadratic relationships in data about Fuel Efficiency, using an inquiry-based model, involving hypothesizing, experimental and computational modeling, and sense-making.

Row and Column Lookups

Students learn how to extract individual rows from a table, and columns from a row.

Exploring Exponential Models

Students investigate exponential relationships in data about Covid spread, using an inquiry-based model involving hypothesizing, experimental and computational modeling, and sense-making. They are introduced to table transformations and inverse functions, which are used to fit exponential models onto nonlinear data.

Exploring Logarithmic Models

Students investigate logarithmic relationships in demographic data about countries of the world, using an inquiry-based model, involving hypothesizing, experimental and computational modeling, and sense-making.

Exploring Periodic Models

Students investigate periodic relationships, first by deciphering the patterns in a dataset with perfect periodic (sinusoidal) behavior and then by looking at data about Carbon Dioxide, using an inquiry-based model involving hypothesizing, experimental and computational modeling, and sense-making.

Student Workbooks

Sometimes, the best place for students to get real thinking done is away from the keyboard! Our lesson plans are tightly integrated with a detailed Student Workbook, allowing for paper-and-pencil practice and activities that don’t require a computer. That’s why we provide a free PDF of the core workbook, as well as a link to the book with every optional exercise included.

Of course, we understand that printing them yourself can be expensive! Click here to purchase beautifully-bound copies of the student workbook from Lulu.com.

Other Resources

Of course, there’s more to a curriculum than software and lesson plans! We also provide a number of resources to educators, including standards alignment, a complete student workbook, an answer key for the programming exercises and a forum where they can ask questions and share ideas.

These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 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.