Teaching Lesson 2
In this lesson, the students will USE the StarLogo Nova Greenhouse Gas model, change a variable to run an experiment, and add code for a slider. In the first activity, the students will learn how to use the model and how to change the variable related to albedo. In the second activity the students will be asked to inspect the code and identify code blocks they are familiar with. In this way they will learn to deconstruct a computer code into its building blocks. They will also be asked to identify new blocks of code, as well as “missing” code. In the third activity, students will add code to make an albedo slider, and then will run an experiment, using the slider. Finally, students will be asked to think of ways to improve the model from home, based on what they know about climate change, greenhouse gases and human emissions of CO2.
Assignment:
Review the activities from Lesson 2 as well as the material below. Reflect on how you would teach this in your class. Post your reflection to your portfolio in "Pedagogy->Module 2" under the heading Lesson 2.
Lesson Objectives
The student will:
Getting Started - 5 minutes
1. Review of the previous day’s lesson and concepts.
Connection to today’s lesson.
Activity #1: Use the Greenhouse Gas base model, change a variable - 10 min.
2. Run the Greenhouse Gas base model.
3. Discuss albedo.
4. Change the variable related to albedo.
Run the model again to see the effect.
Activity #2: Inspect the code – 15 minutes
5. Ask students to identify familiar coding blocks.
6. Assign a part to decode to each pair of students.
7. Program loop and execution order – what calls what?
Activity #3: Add a slider for albedo and run an experiment – 15 minutes
8. Add a slider for albedo.
9. Run an experiment using the albedo slider.
10. Discuss the results and relate them to climate change.
11. Discuss feedback loops.
Wrap Up – 5 minutes
12. Discuss limitations of the model and ask students to think of ways
of improving it.
Assessment Questions
Earth and Human Activity
MS-ESS3-4. Construct an argument supported by evidence for how increases in human population and per-capita consumption of natural resources impact Earth’s systems.
MS-ESS3-5. Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.
NRC Disciplinary Core Ideas
ESS3.C. Human Impacts on Earth Systems
Human activities have significantly altered the biosphere, sometimes damaging or destroying natural habitats and causing the extinction of other species. But changes to Earth’s environments can have different impacts (negative and positive) for different living things. Typically as human populations and per-capita consumption of natural resources increase, so do the negative impacts on Earth unless the activities and technologies involved are engineered otherwise.
ESS3.D. Global Climate Change
Human activities, such as the release of greenhouse gases from burning fossil fuels, are major factors in the current rise in Earth’s mean surface temperature (global warming). Reducing the level of climate change and reducing human vulnerability to whatever climate changes do occur depend on the understanding of climate science, engineering capabilities, and other kinds of knowledge, such as understanding of human behavior and on applying that knowledge wisely in decisions and activities.
NRC Scientific and Engineering Practices
Practice 1. Asking questions and defining problems
1A: Ask questions that arise from careful observation of phenomena, models, or unexpected
1B: Ask questions to identify and clarify evidence of an argument.
1C: Ask questions to determine relationships between independent and dependent variables and relationships in models.
1D: Ask questions to clarify and/or refine a model, an explanation, or an engineering problem.
1F: Ask questions that can be investigated within the scope of the classroom, outdoor environment, and based on observations and scientific principles.
Practice 2. Developing and using models
2A: Evaluate limitations of a model for a proposed object or tool.
2B: Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed.
2C: Use and/or develop a model of simple systems with uncertain and less predictable factors.
2D: Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.
2E: Develop and/or use a model to predict and/or describe phenomena.
2G: Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.
Practice 3. Planning and carrying out investigations
3A: Plan an investigation individually and collaboratively, and in the design: identify independent and dependent variables and controls, what tools are needed to do the gathering, how measurements will be recorded, and how many data are needed to support a claim.
3B: Conduct an investigation and/or evaluate and/or revise the experimental design to produce data to serve as the basis for evidence that meet the goals of the investigation.
3D: Collect data to produce data to serve as the basis for evidence to answer scientific questions or test.
Practice 4. Analyzing and interpreting data
4A: Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
4B: Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.
4D: Analyze and interpret data to provide evidence for phenomena.
4F: Consider limitations of data analysis (e.g., measurement error), and/or seek to improve precision and accuracy of data with better technological tools and methods (e.g., multiple trials).
4G: Analyze and interpret data to determine similarities and differences in findings.
Practice 5. Using Mathematics and Computational Thinking
5D: Apply mathematical concepts and/or processes (e.g., ratio, rate, percent, basic operations, simple algebra) to scientific and engineering questions and problems.
Practice 6. Constructing explanations and designing solutions
6A: Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.
6B: Construct an explanation using models or representations.
6E: Apply scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion.
6F: Apply scientific ideas or principles to design, construct, and/or test a design of an object, tool, process or system.
Practice 7. Engaging in argument from evidence
7C: Construct an oral and written argument supported by empirical evidence and scientific reasoning to support or refute an explanation or a model for a phenomenon or a solution to a problem.
Practice 8. Obtaining, evaluating and communicating information
8E: Communicate scientific and/or technical information (e.g. about a proposed object, tool, process, system) in writing and/or through oral presentations.
NRC Crosscutting Concepts
Patterns
1C: Patterns can be used to identify cause and effect relationships.
1D: Graphs, charts, and images can be used to identify patterns in data.
Cause and Effect
2B: Cause and effect relationships may be used to predict phenomena in natural or designed systems.
2C: Phenomena may have more than one cause, and some cause and effect relationships in systems can only be described using probability
Scale, proportion and quantity
3A: Time, space, and energy phenomena can be observed at various scales using models to study systems that are too large or too small.
Systems and Systems models
4A: Systems may interact with other systems; they may have sub-systems and be a part of larger complex systems.
4B: Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.
4C: Models are limited in that they only represent certain aspects of the system under study.
Energy and Matter
5C: Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).
5D: The transfer of energy can be tracked as energy flows through a designed or natural system.
Stability and Change
7C: Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
Assignment:
Review the activities from Lesson 2 as well as the material below. Reflect on how you would teach this in your class. Post your reflection to your portfolio in "Pedagogy->Module 2" under the heading Lesson 2.
Lesson Objectives
The student will:
- Identify randomness in the model [LO1]
- Understand the concept of albedo and how it relates to climate [LO2]
- Learn about feedback loops in the global climate system [LO3]
- Decode a model [LO4]
- Learn to add a slider [LO5]
- Use the Greenhouse Gas base model to do science and conduct an experiment with repetition [LO6]
- Identify limitations of the model [LO7]
- Practice Pair Programming and Iterative design, implement, test cycle [LO8]
- Make observations (drawing simple correlations) [LO9]
Getting Started - 5 minutes
1. Review of the previous day’s lesson and concepts.
Connection to today’s lesson.
Activity #1: Use the Greenhouse Gas base model, change a variable - 10 min.
2. Run the Greenhouse Gas base model.
3. Discuss albedo.
4. Change the variable related to albedo.
Run the model again to see the effect.
Activity #2: Inspect the code – 15 minutes
5. Ask students to identify familiar coding blocks.
6. Assign a part to decode to each pair of students.
7. Program loop and execution order – what calls what?
Activity #3: Add a slider for albedo and run an experiment – 15 minutes
8. Add a slider for albedo.
9. Run an experiment using the albedo slider.
10. Discuss the results and relate them to climate change.
11. Discuss feedback loops.
Wrap Up – 5 minutes
12. Discuss limitations of the model and ask students to think of ways
of improving it.
Assessment Questions
- Where do we see randomness in the model? [LO1]
- What is the major variable in this model? [LO4]
- What experiment did you run in the model? [LO6]
- Describe your experimental results and conclusions. [LO9]
- What limitations does this model have? [LO7]
- Name three blocks of code you recognized and what they are used for. [LO4]
- What is the slider used for? [LO5]
- List the steps necessary for adding a slider to control a variable. [LO5]
- Give one example of a feedback loop in the global climate system. [LO3]
- Give one example of a human action that could increase or decrease the Earth’s albedo. [LO2]
Earth and Human Activity
MS-ESS3-4. Construct an argument supported by evidence for how increases in human population and per-capita consumption of natural resources impact Earth’s systems.
MS-ESS3-5. Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.
NRC Disciplinary Core Ideas
ESS3.C. Human Impacts on Earth Systems
Human activities have significantly altered the biosphere, sometimes damaging or destroying natural habitats and causing the extinction of other species. But changes to Earth’s environments can have different impacts (negative and positive) for different living things. Typically as human populations and per-capita consumption of natural resources increase, so do the negative impacts on Earth unless the activities and technologies involved are engineered otherwise.
ESS3.D. Global Climate Change
Human activities, such as the release of greenhouse gases from burning fossil fuels, are major factors in the current rise in Earth’s mean surface temperature (global warming). Reducing the level of climate change and reducing human vulnerability to whatever climate changes do occur depend on the understanding of climate science, engineering capabilities, and other kinds of knowledge, such as understanding of human behavior and on applying that knowledge wisely in decisions and activities.
NRC Scientific and Engineering Practices
Practice 1. Asking questions and defining problems
1A: Ask questions that arise from careful observation of phenomena, models, or unexpected
1B: Ask questions to identify and clarify evidence of an argument.
1C: Ask questions to determine relationships between independent and dependent variables and relationships in models.
1D: Ask questions to clarify and/or refine a model, an explanation, or an engineering problem.
1F: Ask questions that can be investigated within the scope of the classroom, outdoor environment, and based on observations and scientific principles.
Practice 2. Developing and using models
2A: Evaluate limitations of a model for a proposed object or tool.
2B: Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed.
2C: Use and/or develop a model of simple systems with uncertain and less predictable factors.
2D: Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.
2E: Develop and/or use a model to predict and/or describe phenomena.
2G: Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.
Practice 3. Planning and carrying out investigations
3A: Plan an investigation individually and collaboratively, and in the design: identify independent and dependent variables and controls, what tools are needed to do the gathering, how measurements will be recorded, and how many data are needed to support a claim.
3B: Conduct an investigation and/or evaluate and/or revise the experimental design to produce data to serve as the basis for evidence that meet the goals of the investigation.
3D: Collect data to produce data to serve as the basis for evidence to answer scientific questions or test.
Practice 4. Analyzing and interpreting data
4A: Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
4B: Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.
4D: Analyze and interpret data to provide evidence for phenomena.
4F: Consider limitations of data analysis (e.g., measurement error), and/or seek to improve precision and accuracy of data with better technological tools and methods (e.g., multiple trials).
4G: Analyze and interpret data to determine similarities and differences in findings.
Practice 5. Using Mathematics and Computational Thinking
5D: Apply mathematical concepts and/or processes (e.g., ratio, rate, percent, basic operations, simple algebra) to scientific and engineering questions and problems.
Practice 6. Constructing explanations and designing solutions
6A: Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.
6B: Construct an explanation using models or representations.
6E: Apply scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion.
6F: Apply scientific ideas or principles to design, construct, and/or test a design of an object, tool, process or system.
Practice 7. Engaging in argument from evidence
7C: Construct an oral and written argument supported by empirical evidence and scientific reasoning to support or refute an explanation or a model for a phenomenon or a solution to a problem.
Practice 8. Obtaining, evaluating and communicating information
8E: Communicate scientific and/or technical information (e.g. about a proposed object, tool, process, system) in writing and/or through oral presentations.
NRC Crosscutting Concepts
Patterns
1C: Patterns can be used to identify cause and effect relationships.
1D: Graphs, charts, and images can be used to identify patterns in data.
Cause and Effect
2B: Cause and effect relationships may be used to predict phenomena in natural or designed systems.
2C: Phenomena may have more than one cause, and some cause and effect relationships in systems can only be described using probability
Scale, proportion and quantity
3A: Time, space, and energy phenomena can be observed at various scales using models to study systems that are too large or too small.
Systems and Systems models
4A: Systems may interact with other systems; they may have sub-systems and be a part of larger complex systems.
4B: Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.
4C: Models are limited in that they only represent certain aspects of the system under study.
Energy and Matter
5C: Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).
5D: The transfer of energy can be tracked as energy flows through a designed or natural system.
Stability and Change
7C: Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
CSTA K-12 Computer Science Standards
|
CT |
Abstraction |
2-12 |
Use abstraction to decompose a problem into sub problems. |
|
CT |
Abstraction |
3A-9 |
Discuss the value of abstraction to manage problem complexity. |
|
CT |
Connections to other fields |
2-15 |
Provide examples of interdisciplinary applications of computational thinking. |
|
CT |
Data representation |
2-8 |
Use visual representation of problem state, structure and data. |
|
CT |
Data representation |
3A-12 |
Describe how mathematical and statistical functions, sets, and logic are used in computation. |
|
CT |
Modeling & simulation |
1:6-4 |
Describe how a simulation can be used to solve a problem. |
|
CT |
Modeling & simulation |
2-9 |
Interact with content-specific models and simulations to support learning and research. |
|
CT |
Modeling & simulation |
2-11 |
Analyze the degree to which a computer model accurately represents the real world. |
|
CT |
Modeling & simulation |
3A-8 |
Use modeling and simulation to represent and understand natural phenomena. |
|
CT |
Modeling & simulation |
3B-8 |
Use models and simulation to help formulate, refine, and test scientific hypotheses. |
|
CT |
Modeling & simulation |
3B-9 |
Analyze data and identify patterns through modeling and simulation. |
|
CPP |
Data collection & analysis |
2-9 |
Collect and analyze data that are output from multiple runs of a computer program. |
|
CPP |
Data collection & analysis |
3B-7 |
Use data analysis to enhance understanding of complex natural and human systems. |
|
CPP |
Data collection & analysis |
3B-8 |
Deploy various data collection techniques for different types of problems. |
|
CPP |
Programming |
3A-3 |
Use various debugging and testing methods to ensure program correctness. |