Teaching Lesson 5
In this lesson, students will finish coding their chosen modifications. Students will then debug their code, checking to make sure it works as they intended, and fixing errors as they find them. In the second activity, students will use their new model as an experimental test bed. They will modify the question they came up with in Lesson 4 if necessary, and they will run experiments to address this question, using replication. Students will critically analyze their results, as well as their model, and relate it back to the bigger picture - climate change. Students will reflect on what modeling with Greenhouse Gases has taught them about climate change and their actions. Students should share their findings with the whole class.
Assignment:
Review the activities from Lesson 5 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 3" under the heading Lesson 5.
Lesson Objectives
The student will:
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-ESS3-4. 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.
ESS2.D. Weather and Climate
Complex interactions determine local weather patterns and influence climate, including the role of the ocean. [Weather and climate are influenced by interactions involving sunlight, the ocean, the atmosphere, ice, landforms and living things. These interactions vary with latitude, altitude, and local and regional geography, all of which can affect oceanic and atmospheric flow patterns. Because these patterns are so complex, weather can only be predicted probabilistically.]
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 results.
1D: Ask questions to clarify and/or refine a model, an explanation, or an engineering problem.
1E: Ask questions that require sufficient and appropriate empirical evidence to answer.
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.
2F: Develop a model to describe unobservable mechanisms.
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.
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.
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).
Practice 5. Using Mathematics and Computational Thinking
5A: Use digital tools (e.g., computers) to analyze very large data sets for patterns and trends.
5B: Use mathematical representations to describe and/or support scientific conclusions and design solutions.
5C: Create algorithms (a series of ordered steps) to solve a problem.
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
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, use, and/or present 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
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
Cause and Effect
Cause and effect relationships may be used to predict phenomena in natural or designed systems.
Stability and Change
Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
Energy and Matter
The transfer of energy can be tracked as energy flows through a designed or natural system.
Patterns
Patterns can be used to identify cause and effect relationships.
Graphs, charts, and images can be used to identify patterns in data.
Scale, proportion and quantity
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
Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.
Models are limited in that they only represent certain aspects of the system under study.
Assignment:
Review the activities from Lesson 5 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 3" under the heading Lesson 5.
Lesson Objectives
The student will:
- Revisit the concept of feedback loops and come up with a possible feedback loop related to human greenhouse gas emissions [LO1]
- Gain a deeper understanding of the effects of human activities on climate change through their experience creating and experimenting with a greenhouse gas model [LO2]
- Gain an understanding of what actions can help mitigate human greenhouse gas emissions [LO3]
- Use their new model as a test bed to run experiments [LO4]
- Learn that the results of their experiments can feed back into the model to improve it [LO5]
- Follow the correct execution of their models and apply debugging techniques to fix the code [LO6]
- Describe one human greenhouse gas emission feedback loop. [LO1]
- What human activities were the greatest drivers of increased temperature in your model? [LO2] How do you think this relates to the real world? [LO2]
- What experiments did you run in the model and why? [LO4]
- What real world information could improve the model? [LO5]
- Define debugging and give an example of some debugging you had to do in your code. [LO6]
- Complete the “USING a Computer Model to do Science” document.
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-ESS3-4. 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.
ESS2.D. Weather and Climate
Complex interactions determine local weather patterns and influence climate, including the role of the ocean. [Weather and climate are influenced by interactions involving sunlight, the ocean, the atmosphere, ice, landforms and living things. These interactions vary with latitude, altitude, and local and regional geography, all of which can affect oceanic and atmospheric flow patterns. Because these patterns are so complex, weather can only be predicted probabilistically.]
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 results.
1D: Ask questions to clarify and/or refine a model, an explanation, or an engineering problem.
1E: Ask questions that require sufficient and appropriate empirical evidence to answer.
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.
2F: Develop a model to describe unobservable mechanisms.
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.
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.
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).
Practice 5. Using Mathematics and Computational Thinking
5A: Use digital tools (e.g., computers) to analyze very large data sets for patterns and trends.
5B: Use mathematical representations to describe and/or support scientific conclusions and design solutions.
5C: Create algorithms (a series of ordered steps) to solve a problem.
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
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, use, and/or present 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
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
Cause and Effect
Cause and effect relationships may be used to predict phenomena in natural or designed systems.
Stability and Change
Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
Energy and Matter
The transfer of energy can be tracked as energy flows through a designed or natural system.
Patterns
Patterns can be used to identify cause and effect relationships.
Graphs, charts, and images can be used to identify patterns in data.
Scale, proportion and quantity
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
Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems.
Models are limited in that they only represent certain aspects of the system under study.
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 |
Abstraction |
3B-10 |
Decompose a problem by defining new functions and classes. |
|
CT |
Algorithms |
3A-3 |
Explain how sequence, selection, iteration and recursion are the building blocks of algorithms. |
|
CT |
Modeling & simulation |
1:6-4 |
Describe how a simulation can be used to solve a problem. |
|
CT |
Modeling & simulation |
2-10 |
Evaluate the kinds of problems that can be solved using modeling and simulation. |
|
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 |
3A-8 |
Use modeling and simulation to represent and understand phenomena. |
|
CT |
Modeling & simulation |
3B-8 |
Use models and simulation to help formulate, refine, and test scientific hypotheses. |
|
CPP |
Programming |
2-5 |
Implement a problem solution in a programming environment using looping behavior, conditional statements, logic, expressions, variables and functions. |
|
CPP |
Programming |
3A-4 |
Apply analysis, design and implementation techniques to solve problems. |