Unit 4. Data Acquisition
Revision Date: Jul 25, 2017 (Version 2.1)Summary
This lesson teaches students to use simulations to develop, refine and test hypotheses. NetLogo, which is used throughout the lesson to illustrate the use of functional and data abstraction, is a programmable modeling environment for simulating natural and social phenomena.
NetLogo is a variation of the Logo language instead of Python, so students are not expected to write new code in this lesson. See http://www.ianbicking.org/docs/PyLogo_lightning.html for a comparison of Logo and Python.
Outcomes
Students will understand that models are abstractions of real environments and will recognize the rationale for, and limitations of, modeling techniques to analyze problems.
Students will recognize the use of functional and data abstractions in modeling.
Students will be able to develop and test hypotheses using an experimental approach in a modeling framework.
Overview
Session 1 - Modeling in NetLogo
Session 2 - Models and Hypothesis Design
Session 3 - Hypothesis Testing
Note: This lesson introduces another programming tool and environment: NetLogo. Teachers may choose to complete only the first session (on the basics of NetLogo), to expose students to a new computational platform and way of thinking, to extend the ideas in Unit 4 about modeling and simulation.
Students will understand that models are an abstraction of real environments and will recognize the rationale for and limitations of modeling techniques to analyze problems.
Students will recognize the use of functional and data abstractions in modeling.
Students will be able to develop and test hypotheses using an experimental approach in a modeling framework.
Student computer usage for this lesson is: required
NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL. NetLogo tutorial packet online web version http://ccl.northwestern.edu/netlogo/docs/
Modeling and Simulation 101 video ( https://www.youtube.com/watch?v=X-6zxImekOE )
See http://www.ianbicking.org/docs/PyLogo_lightning.html for a comparison of Logo, PyLogo and Python.
New Mexico "Computer Science for All" bases the entire course on modeling and simulation using NetLogo http://www.cs4all.org/NM-CS108L-Week3-Final
Question: Describe something that can be modeled using a simulation.
Introduce modeling and simulation using the first four minutes of the Modeling and Simulation 101 video ( https://www.youtube.com/watch?v=X-6zxImekOE ). Students open a document for notes for today's session.
Students should record and briefly discuss these four statements about modeling and simulation:
To start, all students should download NetLogo from this link http://ccl.northwestern.edu/netlogo/ or use the web version of the program.
Students should work through the NetLogo tutorial packet either in groups or as a class.
In particular, students should be encouraged to notice commonalities in programming languages (sequence, conditionals, iteration, abstraction) and how differences in languages provide specific tools best suited to particular problems. The domain of modeling and simulation is a huge area in computational thinking, and NetLogo is one of many languages well suited to problem-solving in this domain. Point out that Python is used for modeling and simulation, but to be clear and readable requires the abstraction of libraries to build on that provide the same functionality that comes with a language like NetLogo.
There will be some "thought questions" throughout that students should discuss in their groups and as a class.
Students should complete an exit ticket listing one interesting idea they learned, or one question they have about NetLogo or modeling.
Review yesterday's NetLogo lesson and ask the students to share what they learned, how NetLogo is similar to or different from Python, and any questions they have about how it works. Point out that it is the ABSTRACTION available in NetLogo that makes it easier to read and write simulation programs because it has features built into it that are readily available that you can build on. This PowerPoint details the abstractions in NetLogo with the accompanying transcript from CS for All in New Mexico. List abstractions available in Python that are different from NetLogo or PyLogo. What is built into each language that makes it easy to use?
Ask each student to write a hypothesis that can be tested with this simulation, share the hypothesis with elbow partners, and briefly experiment with the parameters to informally test the hypothesis.
Note: The "Hypothesis Testing Worksheet" which will be used for the next two lessons is available in the Lesson Resources Folder
For the rest of today's session and Session 3, students will work in teams of four students to select a model to experiment with, then divide into two partner sets to develop a hypothesis, devise an experimental plan, test the hypothesis, and write about their results.
Directions
Partners should revisit their hypotheses, and choose one hypothesis to focus on first. (They can test both hypotheses if they have time.) Each partner pair should write the name of their model and their selected hypothesis on the board, to share with the other students.
For the next twenty to thirty minutes, students should carry out their experiments and record the appropriate measurements.
At the end of the section or for homework, students should write up their findings in a short report, showing the data they've collected (optionally in a graphical form, particularly if assigned as homework), discussing what the data says about their hypothesis, and concluding whether the hypothesis is supported or refuted by the simulation.
Students should come back into their teams to share their findings, and discuss the advantages and disadvantages of using models and simulations to develop and test hypotheses.
Students will share and post their hypothesis before testing and sharing the results. Teachers will verify that the hypothesis are falsifiable and testable by the simulations.
Students will select a model, develop a hypothesis, design an experiment, and use a simulation to test the hypothesis.