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New York
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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.
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- I can identify a few obvious ways crowding, ventilation, and resource use may affect classroom air quality, but my explanation is mostly based on isolated observations or general ideas
- I can name a basic criterion or constraint for a classroom air solution, though I need support to connect evidence, compare options, or explain how human population and resource use affect Earth systems.
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- I can use some relevant data and observations to explain how crowding, airflow, and resource use contribute to indoor air pollution hotspots in classrooms
- I can define key criteria and constraints for a prototype and compare two design ideas using evidence, though my reasoning may still be incomplete or uneven.
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- I can analyze classroom air-quality, occupancy, and ventilation data to explain patterns, causes, and impacts of pollution hotspots, including how human population density and per-capita resource use can affect Earth systems and school environments
- I can define precise criteria and constraints, evaluate competing solutions with a systematic process, and use test data to revise my prototype based on strengths and weaknesses.
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- I can construct a clear, evidence-based argument that links human population density and per-capita resource consumption to changes in Earth systems and to indoor air-quality challenges in crowded NYC schools
- I can synthesize data from multiple tests and sources to compare solutions, identify the best features of each, and justify an improved model that meets criteria and constraints while showing thoughtful, critical decision-making.
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New York
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MS-ETS1-1 - Define the criteria and constraints of a design problem with sufficient precision to ensure a successful solution, taking into account relevant scientific principles and potential impacts on people and the natural environment that may limit possible solutions.
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- I can identify a simple classroom air-quality problem and name a few obvious criteria or constraints, such as space, safety, cost, or airflow, but my ideas may be incomplete or not yet connected to science evidence
- I can make a basic attempt to explain how crowding or resource use might affect the problem, though my reasoning is mostly general or needs support.
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- I can define the classroom air-pollution design problem with some clear criteria and constraints and use a few observations or data points to explain why they matter
- I can begin to connect human population density, resource use, and indoor air conditions, and I can describe how these factors may limit possible solutions in crowded NYC schools.
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- I can define the design problem with clear and relevant criteria and constraints, using scientific principles and evidence from observations, interviews, or data to support my choices
- I can explain how crowding, ventilation, and resource use contribute to pollution hotspots and identify impacts on people and the natural environment that affect solution options.
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- I can define the design problem with precise, well-justified criteria and constraints that reflect scientific principles, stakeholder needs, and real conditions in crowded NYC schools
- I can critically evaluate evidence from multiple sources, connect patterns in the data to human population and resource use, and clearly explain how these factors shape and limit the best possible solution.
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New York
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MS-ETS1-2 - Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem.
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- I can identify one or two possible classroom air-quality design solutions and name a few obvious criteria or constraints, but my comparison is mostly based on general opinions or a single piece of evidence
- I need support to explain how well each solution fits the problem of reducing pollution hotspots in crowded NYC classrooms.
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- I can compare at least two design solutions using some relevant criteria and constraints, and I can describe basic strengths and weaknesses of each using evidence from tests, observations, or data
- I can explain which solution seems better overall, though my reasoning may not yet consider all impacts or trade-offs.
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- I can evaluate competing design solutions with a systematic process, using multiple criteria and constraints such as air movement, filtration effectiveness, safety, cost, space, and maintenance
- I can cite test data and observations to justify why one solution performs better than another and identify specific features that should be improved or combined.
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- I can evaluate and rank several design solutions with a clear, consistent process that weighs evidence, trade-offs, and impacts on people and the environment
- I can explain how my chosen solution best meets the criteria and constraints for crowded NYC schools, and I can use precise data analysis to recommend the strongest features for a revised model.
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New York
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MS-ETS1-3 - Analyze data from tests to determine similarities and differences among several design solutions to identify the best characteristics of each that can be combined into a new solution to better meet the criteria for success.
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- I can identify basic similarities and differences in test results from one or more classroom air-flow or filtration prototypes, but I may need help interpreting the data or connecting it to the problem
- I can point to a few features that seem to work or not work, but my choices are not yet fully supported by evidence or tied to the criteria and constraints for crowded NYC classrooms.
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- I can compare test data from multiple design solutions and describe how each one performs against the main criteria and constraints, such as airflow, filtration, cost, space, safety, and maintenance
- I can use evidence to choose a few useful features from different solutions and explain how they could improve a revised model for reducing pollution hotspots.
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- I can analyze test data from several design solutions to clearly identify patterns, similarities, and differences in performance
- I can use that evidence to determine the best characteristics from each solution and combine them into a revised model that better meets the criteria and constraints for healthier, crowded NYC classrooms.
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- I can independently and thoughtfully analyze repeated test data from multiple design solutions to explain which design features are most effective and why, including trade-offs related to people and the natural environment
- I can justify how I selected and combined the strongest characteristics into a refined model that best meets the criteria and constraints and demonstrates a sophisticated, evidence-based engineering decision as an environmental engineer.
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New York
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MS-ETS1-4 - Develop a model to generate data for iterative testing and modification of a proposed object, tool, or process such that an optimal design can be achieved.
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- I can build a very simple airflow or filtration model and describe what it is meant to test
- I can follow directions to make one change at a time, but my model may not yet generate clear data for comparing how well it reduces pollution hotspots or meets the design criteria and constraints.
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- I can build and test a small-scale classroom air-flow or filtration prototype that produces some usable data
- I can use evidence from my trials to explain what worked, what did not, and what I should revise, though my model or testing process may still be inconsistent or only partly aligned to the criteria and constraints.
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- I can develop and test a clear model for reducing indoor air pollution hotspots, collect repeated data, and compare results to the project criteria and constraints
- I can use patterns in the data and feedback from others to make logical revisions that improve my design for crowded NYC classrooms.
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- I can create a well-justified model that generates reliable data for iterative testing and revision, and I can use that evidence to refine an optimal solution
- I can analyze similarities and differences across design trials, explain why my revisions improve performance, and connect my choices to scientific principles, human impacts, and the needs of crowded NYC schools.
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