Teaching Lesson 2

In this lesson, students will become familiar with the Water Pumping base model. In the first activity students will review math basics necessary for understanding the model. In the second activity students will decode the base model and run simple experiments, make observations, and
identify a complex systems characteristic of the model. In the third activity, students will add an evaporation slider, and then will run an experiment, using the slider. Finally, students will be asked to think of ways to improve the model, based on what they know about the hydrologic cycle and water as a resource.

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 an emergent pattern in the water pump model [LO5].
  • Learn that water continually cycles among land, ocean, and atmosphere [LO6].
  • Identify abstractions made and limitations of the model [LO7].
  • Use the Water Pumping base model to conduct a repeated experiment and make
  • observations (drawing simple correlations) [LO8].
  • Decode a model [LO9].
  • Trace a program’s execution [LO10].

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

Activity #1: Review math basics for modeling – 15 minutes
     2. Review coordinates on a graph; connect coordinate system to Spaceland.
     3. Create turtles in different quadrants of Spaceland and use new blocks to make turtles move in a specific direction.

Activity #2: Under the Hood: Inspecting the Water Pumping model – 10 minutes
     4. Identify familiar coding blocks
     5. Decode model in pairs.

Activity #3: Add a slider for evaporation and run an experiment – 15 minutes
     6. Add a slider for evaporation.
     7. Run an experiment using the evaporation slider.
     8. Discuss the results and relate them to the hydrologic cycle.

Wrap-Up – 5 minutes
     9. Discuss limitations of the model and think of ways of improving it.

Assessment Questions
  • What is an emergent pattern being formed when we run the model? [LO5]
  • Identify which part(s) of the water cycle is represented in the Water Pumping model? [LO6]
  • What are some of the abstractions or simplifications made in the model? [LO7]
  • What were some of the observations you made as you ran the model? [LO8]
  • Name three blocks of code you recognized and what each one does [LO9].
  • List the steps the program executes in order in the forever loop [LO10].

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 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
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.

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.