Building on their understanding of graphs, students are introduced to random processes on networks. They walk through an illustrative example to see how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students. This demonstrates how scientists and engineers use mathematics to model and simulate random processes on complex networks. Topics covered include random processes and modeling disease spread, specifically the SIR (susceptible, infectious, resistant) model.

This template supports STEM teachers and librarians in working collaboratively to create lessons that build science practice and STEM inquiry skills in alignment with state and national science standards, and that address the Common Core literacy shifts around close reading and building textual evidence.

In this lesson designed to enhance literacy skills, students study a disease outbreak and the investigation that followed to understand the role that public health workers play in protecting the communities they serve.

In this lesson designed to enhance literacy skills, students examine our growing waste problem and learn about strategies we can use to lessen the strain on our landfills and Earth's natural resources: reduce, reuse, recycle.

This is a teaching activity in which students learn about the connection between CO2 emissions, CO2 concentration, and average global temperatures. Through a simple online model, students learn about the relationship between these and learn about climate modeling while predicting temperature change over the 21st century.

Students will gather information and data about vaccine information. They will use this information to argue whether or not vaccinations should be mandatory, culminating in a summative assessment in the form of a debate and a reflection on the information gathered.

Prepared with pre-algebra or algebra 1 classes in mind, this module leads students through the process of graphing data and finding a line of best fit while exploring the characteristics of linear equations in algebraic and graphic formats. Then, these topics are connected to real-world experiences in which people use linear functions. During the module, students use these scientific concepts to solve the following hypothetical challenge: You are a new researcher in a lab, and your boss has just given you your first task to analyze a set of data. It being your first assignment, you ask an undergraduate student working in your lab to help you figure it out. She responds that you must determine what the data represents and then find an equation that models the data. You believe that you will be able to determine what the data represents on your own, but you ask for further help modeling the data. In response, she says she is not completely sure how to do it, but gives a list of equations that may fit the data. This module is built around the legacy cycle, a format that incorporates educational research feindings on how people best learn.