Lesson 4. Animal Behavior Computational Lab: Part 1

Teresa Granito, Sugat Dabholkar, Mandy Peel, Shruti Researcher
Biology
4 class periods (45 minute periods)
High School Advanced Placement (AP) Biology
v5

Overview

In this lesson, you will start the computational lab.

Please keep in mind that some of the activities/questions are designed expecting that you have done the physical lab. You can attempt those questions based on your expectations about the physical lab or you can skip those questions.

In this lesson, you will learn the following science practices using computational tools:

Science Practice 1

The student can use representations and models to communicate scientific phenomena and solve scientific problems.

Science Practice 2

The student can use mathematics appropriately.

Science Practice 3

The student can engage in scientific questioning to extend thinking or to guide investigations within the context of the AP course.

Science Practice 4

The student can plan and implement data collection strategies in relation to a particular scientific question. (Note: Data can be collected from many different sources, e.g., investigations, scientific observations, the findings of others, historic reconstruction and/or archived data.)

Science Practice 5

The student can perform data analysis and evaluation of evidence.

Standards

Next Generation Science Standards
  • Life Science
    • [HS-LS2] Ecosystems: Interactions, Energy, and Dynamics
    • [HS-LS4] Biological Evolution: Unity and Diversity
  • NGSS Crosscutting Concept
    • Patterns
    • Causation
    • Scale
    • Systems
    • Stability and Change
  • NGSS Practice
    • Analyzing Data
    • Communicating Information
    • Constructing Explanations, Designing Solutions
    • Asking Questions, Defining Problems
    • Using Models
    • Using Mathematics
    • Arguing from Evidence
    • Conducting Investigations
Computational Thinking in STEM
  • Data Practices
    • Analyzing Data
    • Collecting Data
    • Creating Data
    • Manipulating Data
    • Visualizing Data
  • Modeling and Simulation Practices
    • Assessing Computational Models
    • Designing Computational Models
    • Using Computational Models to Find and Test Solutions
    • Using Computational Models to Understand a Concept
    • Constructing Computational Models
  • Computational Problem Solving Practices
    • Assessing Different Approaches/Solutions to a Problem
    • Creating Computational Abstractions
    • Developing Modular Computational Solutions
    • Computer Programming
    • Troubleshooting and Debugging
    • Preparing Problems for Computational Solutions
  • Systems Thinking Practices
    • Communicating Information about a System
    • Investigating a Complex System as a Whole
    • Thinking in Levels
    • Understanding the Relationships within a System

Credits

This curricular unit is co-designed by Teresa Granito and Sugat Dabholkar.

Activities

  • 1. Experimental design: Part 1
  • 2. Experimental design: Part 2
  • 3. Using a computational model for scientific inquiry
  • 4. Designing and Constructing a Computational Model
  • 5. Assessing computational models

Student Directions and Resources


You are expected to do this computational lab after you have finished the physical (wet) experimental lessons. 

If you have not done the physical animal behavior lab, you can still go ahead. However, please keep in mind that some of the activities/questions are designed expecting that you have done the physical lab. You can attempt those questions based on your expectations about the physical lab or you can skip those questions.

In this lesson, you will learn the following science practices using computational tools:

Science Practice 1

The student can use representations and models to communicate scientific phenomena and solve scientific problems.

Science Practice 2

The student can use mathematics appropriately.

Science Practice 3

The student can engage in scientific questioning to extend thinking or to guide investigations within the context of the AP course.

Science Practice 4

The student can plan and implement data collection strategies in relation to a particular scientific question. (Note: Data can be collected from many different sources, e.g., investigations, scientific observations, the findings of others, historic reconstruction and/or archived data.)

Science Practice 5

The student can perform data analysis and evaluation of evidence.

 

1. Experimental design: Part 1


The model below is of an experimental setup to study habitat preference of a certain type of isopods called rollypollies.


Question 1.1

Explore the model above. Change conditions and other parameters.

Write at least two observations that you found interesting or surprising.



Question 1.2

You will run the model below after you answer this question. What will happen if you set up the conditions as 10 rollypollies and the two chambers with the same condition (dry/dry or moist/moist) then run for 30 ticks. Write your prediction regarding the distribution of roly-polies in the two chambers.

Don't run the model before you answer this question.



Question 1.3

Test your prediction. 

  • Start the model with 10 roly-polies. 
  • Set the same conditions in both chambers. 
  • Run the model for 30 ticks. 

Did your results match your prediction?  Why or why not?



Question 1.4

Suppose we increase the number of roly-polies to 20, run for 30 ticks and repeat.

Suppose we increase the number of roly-polies to 40, run for 30 ticks and repeat.

What do you think will happen? Run the model. 

Record your observations about increasing the number of roly-polies.  How does this data compare to your prediction in Question 1.2?

2. Experimental design: Part 2


Let's discover what happens as you increase the number of ticks.


Question 2.1

Set chambers to dry/dry. Start with 20 roly-polies. Time for 5 ticks, make observations. Repeat at least three times.

Record your observations.



Question 2.2

Make a prediction regarding the distribution of roly-polies when you change in the amount of time. Write predicted results when you increase the amount of time.



Question 2.3

Run the model for 30 ticks.  Make observations and repeat the experiment at least 3 times.

Run the model for 1000 ticks.  Make observations and repeat the experiment at least 3 times.

What conclusion can you make based on your observations?

3. Using a computational model for scientific inquiry



Question 3.1

In this activity, you will use a computational model to design and conduct your own experiment investigating isopod behavior.

Pick conditions for each of your chambers.



Question 3.2

Set the number of roly-polies for your experiment.

Set the number of ticks.



Question 3.3

Explain the reasons for your choices in the previous two questions.



Question 3.4

Run the model.

Record your observations here.

4. Designing and Constructing a Computational Model



Question 4.1

Collect class data about roly-poly preference from the physical lab (actual experiments with real-world roly-polies). If you have not done the physical (wet) lab, find out the answer using google search. Make sure you use reliable information from the web.

What conditions did the roly-polies prefer?

  Neutral pH
  Acidic pH
  Basic pH
  No leaf litter
  Leaf litter
  Soil
  No soil
  Dark
  Light
  Saltwater
  Freshwater
  Food
  No Food
  Other


Question 4.2

Chose the conditions you want to test with the computational model.

Write your conditions here.



Question 4.3

Now you will code new conditions into the model.

Follow the directions.  The screenshots will guide you.

You just modified code and created a new experimental model! Describe your experience.



Question 4.4

Ask a Scientific Question that can be assessed by your new model. Write the question.



Question 4.5

Make a prediction based on your new conditions. Write your prediction.



Question 4.6

Describe your experimental design (initial conditions - number of roly-polies and chamber preference, and the number of ticks).

Explain the reasons for your choices of experimental conditions.



Question 4.7

Run the experiment. Write your observations.



Question 4.8

Do your predictions match the results of the model?  State your evidence.



Question 4.9

Explain what you learned in the process of making modifications to this model.



Question 4.10

What did you learn about computational modeling after you performed investigations on this page?

5. Assessing computational models



Question 5.1

How do the results from the computational models compare with the roly-poly experiment you conducted?



Question 5.2

What are some advantages of using computational models to predict animal behavior vs the physical lab experiments we conducted at the beginning of the unit?



Question 5.3

What are some limitations of the computation models used in this unit?  What are some limitations to the physical lab?



Question 5.4

How can a computational model aid a scientist with their work?



Question 5.5

Write at least one big idea that you learned in this lesson.