CT-STEM

Overview

In this lesson, you will continue with 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. Explore Computationally Enhanced Data Collection
2. Conduct computationally enhanced automated experimental trials
3. Reflection

Student Directions and Resources

In this lesson, you will learn how to use automated tools for data collection.

1. Explore Computationally Enhanced Data Collection

Scroll to the right to see the results table.

Warning alert: After you finish questions on this page and you click Save and Continue, you will receive an error message about leaving this page because your data table has not been saved. You can click Leave without saving. All other responses will be saved.

Question 1.1

How is this computational experimental setup different from the one in the previous lesson? Write down any different features and what you think they do.

Question 1.2

Play around with the model and design your protocol for data collection.

Your protocol design should include the initial conditions, the number of trials, and the time interval between two readings.

Write your design here.

Question 1.3

Run an experimental trial with your protocol and upload a screenshot.

Upload files that are less than 5MB in size.

File	Delete

Upload files to the space allocated by your teacher.

Question 1.4

Use CODAP to find means and standard deviations of the numbers of roly-polies in each chamber. See the video to understand how to use CODAP. [If the video is not displayed below, please ask your teacher to screen the video.]

Question 1.5

What are the advantages of using a computationally automated data collection tool?

2. Conduct computationally enhanced automated experimental trials

Note: The button "run for 30 ticks" makes the model run continuously at '30 ticks increments'.

Question 2.1

Play around with the model and design an elaborate experimental protocol.

[Hint: Explicitly state experimental conditions like “number-of-readings”]