Teaching Lesson 4

In this lesson, students design their own Water Pumping projects consisting of a question, experimental design and model. In the first activity, students will learn about computational science and how to design a model, and will use this knowledge to scope their project. This leads to a second activity, in which they start designing and implementing their model, using the Water Pumping base model as a starting place.

Review the activities from Lesson 4 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 4.

Lesson Objectives
The student will:
  • Learn that resources are distributed unevenly around the planet as a result of past geologic processes [LO17].
  • Learn that Humans depend on water resources and many of these resources are not renewable or replaceable over human lifetimes [LO18].
  • Use the key stages of computational science and Project Design Form to develop a question, create a model, and design an experiment [LO19].
  • Implement problem solutions using looping behavior, conditional statements, logic, expressions, variables and functions [LO20].

Teaching Summary
Getting Started – 5 minutes
     1. Review of the previous day’s lesson and concepts and connection to today’s lesson

Activity #1: Computational Science and Model Design – 20 minutes
     2. Introduce key components of the computational science process
     3. Define your computational science project

Activity #2: Design and develop your model – 20 minutes
     4. Agents and environment
     5. Interactions

Wrap-Up – 5 minutes
     6. What research is necessary to ground your model in reality?
     7. How will you check to see if your model is realistic?

Assessment Questions
  • Give three examples of how local conditions affect water supply or quality [LO17].
  • Describe why some water is not renewable or replaceable; where does the water go? [LO18]
  • See student Project Design Form. (Did student choose a question appropriate for answering with the model? Could student explain why it was chosen? Did student describe the aspects of the real world to be included in the model and why they were selected? etc.) [LO19]
  • Describe procedures in the model that you built. Choose one and describe how it works in detail [LO20].

NGSS Performance Expectations
Earth and Human Activity
MS-ESS3-3.Apply scientific principles to design a method for monitoring and minimizing a human impact on the environment.
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.

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.

NRC Scientific and Engineering Practice Standards
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
8C: Gather, read, and synthesize information from multiple appropriate sources and assess the credibility, accuracy, and possible bias of each publication and methods used, and describe how they are supported or not supported by evidence.

NRC Crosscutting Concepts
1. Patterns:
1C: Patterns can be used to identify cause and effect relationships.

2. Cause and Effect:
2B: Cause and effect relationships may be used to predict phenomena in natural or designed systems.

4. Systems and Systems models
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.

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 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.