Using Avida-ED freeware, students control a few factors in an environment populated with digital organisms, and then compare how changing these factors affects population growth. They experiment by altering the environment size (similar to what is called carrying capacity, the maximum population size that an environment can normally sustain), the initial organism gestation rate, and the availability of resources. How systems function often depends on many different factors. By altering these factors one at a time, and observing the results, students are able to clearly see the effect of each one.
In this activity, students use an old fashion children's toy, a metal slinky, to mimic and understand the magnetic field generated in an MRI machine. The metal slinky mimics the magnetic field of a solenoid, which forms the basis for the magnet of the MRI machine. Students run current through the slinky and use computer and calculator software to explore the magnetic field created by the slinky.
Modeling Our World with Mathematics Unit 1: Health & Fitness Topic 2 - Sports & Fitness
Modeling Our World with Mathematics Unit 3: Civic Readiness Topic 1 - The United States Census
This is a task from the Illustrative Mathematics website that is one part of a complete illustration of the standard to which it is aligned. Each task has at least one solution and some commentary that addresses important asects of the task and its potential use. Here are the first few lines of the commentary for this task: The scatterplot below shows the finishing times for the Olympic gold medalist in the men's 100-meter dash for many previous Olympic games. The least sq...
As part of the engineering design process to create testable model heart valves, students learn about the forces at play in the human body to open and close aortic valves. They learn about blood flow forces, elasticity, stress, strain, valve structure and tissue properties, and Young's modulus, including laminar and oscillatory flow, stress vs. strain relationship and how to calculate Young's modulus. They complete some practice problems that use the equations learned in the lesson mathematical functions that relate to the functioning of the human heart. With this understanding, students are ready for the associated activity, during which they research and test materials and incorporate the most suitable to design, build and test their own prototype model heart valves.
This web-based graphing activity explores the similarities and differences between Velocity vs. Time and Position vs. Time graphs. It interactively accepts user inputs in creating "prediction graphs", then provides real-time animations of the process being analyzed. Learners will annotate graphs to explain changes in motion, respond to question sets, and analyze why the two types of graphs appear as they do. It is appropriate for secondary physical science courses, and may also be used for remediation in preparatory high school physics courses. This item is part of the Concord Consortium, a nonprofit research and development organization dedicated to transforming education through technology. Users must register to access full functionality of all the tools available with SmartGraphs.
In this module, students reconnect with and deepen their understanding of statistics and probability concepts first introduced in Grades 6, 7, and 8. Students develop a set of tools for understanding and interpreting variability in data, and begin to make more informed decisions from data. They work with data distributions of various shapes, centers, and spreads. Students build on their experience with bivariate quantitative data from Grade 8. This module sets the stage for more extensive work with sampling and inference in later grades.
This is a task from the Illustrative Mathematics website that is one part of a complete illustration of the standard to which it is aligned. Each task has at least one solution and some commentary that addresses important asects of the task and its potential use. Here are the first few lines of the commentary for this task: Jane wants to sell her Subaru Forester and does research online to find other cars for sale in her area. She checks on craigslist.com and finds 22 Suba...
This lesson unit is intended to help teachers assess how well students understand the notion of correlation. In particular this unit aims to identify and help students who have difficulty in: understanding correlation as the degree of fit between two variables; making a mathematical model of a situation; testing and improving the model; communicating their reasoning clearly; and evaluating alternative models of the situation.
Following the steps of the iterative engineering design process, student teams use what they learned in the previous lessons and activity in this unit to research and choose materials for their model heart valves and test those materials to compare their properties to known properties of real heart valve tissues. Once testing is complete, they choose final materials and design and construct prototype valve models, then test them and evaluate their data. Based on their evaluations, students consider how they might redesign their models for improvement and then change some aspect of their models and retest aiming to design optimal heart valve models as solutions to the unit's overarching design challenge. They conclude by presenting for client review, in both verbal and written portfolio/report formats, summaries and descriptions of their final products with supporting data.
This task addresses many standards regarding the description and analysis of bivariate quantitative data, including regression and correlation. Students should recognize that the pattern shown is one of a strong, positive, linear association, and thus a correlation coefficient value near +1 is plausible. Students should also be able to interpret the slope of the least-squares line as an estimated increase in y per unit change in x (and thus for a 3 unit increase in x, students should expect an estimated increase in y that equals 3 times the model's slope value).
Students analyze the relationship between wheel radius, linear velocity and angular velocity by using LEGO(TM) MINDSTORMS(TM) NXT robots. Given various robots with different wheel sizes and fixed motor speeds, they predict which has the fastest linear velocity. Then student teams collect and graph data to analyze the relationships between wheel size and linear velocity and find the angular velocity of the robot given its motor speed. Students explore other ways to increase linear velocity by changing motor speeds, and discuss and evaluate the optimal wheel size and desired linear velocities on vehicles.
Modeling Our World with Mathematics Unit 2: Environmental Science Topic 2 - Sustainable Forestry
Modeling Our World with Mathematics Unit 2: Environmental Science Topic 1 - Air Quality
The purpose of this task is to assess ability to interpret the slope and intercept of the least squares regression line in context.
Modeling Our World with Mathematics Unit 1: Health & Fitness Topic 1 - A Healthier You!
Explore how populations change over time in a NetLogo model of sheep and grass. Experiment with the initial number of sheep, the sheep birthrate, the amount of energy sheep gain from the grass, and the rate at which the grass re-grows. Remove sheep that have a particular trait (better teeth) from the population, then watch what happens to the sheep teeth trait in the population as a whole. Consider conflicting selection pressures to make predictions about other instances of natural selection.
This lesson unit is intended to help teachers assess how well students are able to: interpret data and evaluate statistical summaries; and critique someone elseŐs interpretations of data and evaluations of statistical summaries. The lesson also introduces students to the dangers of misapplying simple statistics in real-world contexts, and illustrates some of the common abuses of statistics and charts found in the media.
A statistics lesson on describing and making claims from data representations, specifically linearly increasing data. Applies ideas of rate-of-change to develop writing a linear equation to fit the data, using the equation to interpolate and extrapolate additional information, and integrating the mathematical interpretation appropriately into a social sciences argument.