# Stopping Superbugs!

6th-8th
Group Size
4-6 students
Active Time
60 minutes
Total Time
60 minutes
Area of Science
Human Biology & Health
Microbiology
Key Concepts
Genetics, Bacteria, Probability, Antibiotic resistance
Learning Objectives
• Understand how natural selection leads to the predominance of certain traits in a bacterial population
• Correlate misuse of antibiotics with an increased probability of creating antibiotic-resistant bacteria
• Apply a model using probability to simulate how bacteria populations change in response to selective pressure
Credits
Svenja Lohner, PhD, Science Buddies

## Overview

If your doctor prescribes antibiotics, why do you have to take them for several days and not just once? Why do you need to finish taking them even if you feel better? If you do not follow the doctor's orders, you might contribute to the creation of antibiotic-resistant "superbugs"! In this lesson, your students will roll dice to model how bacteria respond to treatment by antibiotics, and find out what happens if treatment is stopped too early.

## NGSS Alignment

This lesson helps students prepare for these Next Generation Science Standards Performance Expectations:
• MS-LS4-4. Construct an explanation based on evidence that describes how genetic variations of traits in a population increase some individuals' probability of surviving and reproducing in a specific environment.
• MS-LS4-6. Use mathematical representations to support explanations of how natural selection may lead to increases and decreases of specific traits in populations over time.
This lesson focuses on these aspects of NGSS Three Dimensional Learning:

 Science & Engineering Practices Disciplinary Core Ideas Crosscutting Concepts Developing and Using Models. Develop and/or use a model to predict and/or describe phenomena. Analyzing and Interpreting Data. Analyze and interpret data to provide evidence for phenomena. Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible. Using Mathematics and Computational Thinking. Apply mathematical concepts and/or processes (e.g., ratio, rate, percent, basic operations, simple algebra) to scientific and engineering questions and problems. LS4.B: Natural Selection. Natural selection leads to the predominance of certain traits in a population, and the suppression of others. LS4.C: Adaptation. Adaptation by natural selection acting over generations is one important process by which species change over time in response to changes in environmental conditions. Traits that support successful survival and reproduction in the new environment become more common; those that do not become less common. Thus, the distribution of traits in a population changes. Cause and Effect. Phenomena may have more than one cause, and some cause and effect relationships in systems can only be described using probability. Systems and System Models. Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.

## Materials

Materials per group of 4–6 students:

• Six-sided dice (100 total), in three different colors; available at Amazon.com:
• 70 of one color (purple in the picture)
• 25 of a second color (green in the picture)
• 5 of a third color (red in the picture)
• Pot, box, or sealable plastic bag that is large and sturdy enough to hold all 100 dice. If you use a metal pot, you may also want to use a lid to cut down on the noise of rolling the dice.
• Large, flat surface for pouring 100 dice onto
• Pencil or pen

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6th-8th
Group Size
4-6 students
Active Time
60 minutes
Total Time
60 minutes
Area of Science
Human Biology & Health
Microbiology
Key Concepts
Genetics, Bacteria, Probability, Antibiotic resistance
Credits
Svenja Lohner, PhD, Science Buddies
Learning Objectives
• Understand how natural selection leads to the predominance of certain traits in a bacterial population
• Correlate misuse of antibiotics with an increased probability of creating antibiotic-resistant bacteria
• Apply a model using probability to simulate how bacteria populations change in response to selective pressure
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