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.

Evidence Statements for MS-ETS1-1:

1. Identifying the problem to be solved

a. Students describe* a problem that can be solved through the development of an object, tool, process, or system.

2. Defining the process or system boundaries and the components of the process or system

a. Students identify the system in which the problem is embedded, including the major components and relationships in the system and its boundaries, to clarify what is and is not part of the problem. In their definition of the system, students include:

i. Which individuals or groups need this problem to be solved.

ii. The needs that must be met by solving the problem.

iii. Scientific issues that are relevant to the problem.

iv. Potential societal and environmental impacts of solutions.

v. The relative importance of the various issues and components of the process or system.

3. Defining criteria and constraints

a. Students define criteria that must be taken into account in the solution that:

i. Meet the needs of the individuals or groups who may be affected by the problem (including defining who will be the target of the solution).

ii. Enable comparisons among different solutions, including quantitative considerations when appropriate.

b. Students define constraints that must be taken into account in the solution, including:

i. Time, materials, and costs.

ii. Scientific or other issues that are relevant to the problem.

iii. Needs and desires of the individuals or groups involved that may limit acceptable solutions.

iv. Safety considerations.

v. Potential effect(s) on other individuals or groups.

vi. Potential negative environmental effects of possible solutions or failure to solve the problem.

MS-ETS1-2:  Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem. 

Evidence Statements for MS-ETS1-2

1. Identifying the given design solution and associated claims and evidence

a. Students identify the given supported design solution.

b. Students identify scientific knowledge related to the problem and each proposed solution.

c. Students identify how each solution would solve the problem.

2. Identifying additional evidence

a. Students identify and describe* additional evidence necessary for their evaluation, including:

i. Knowledge of how similar problems have been solved in the past.

ii. Evidence of possible societal and environmental impacts of each proposed solution.

b. Students collaboratively define and describe* criteria and constraints for the evaluation of the design solution.

3. Evaluating and critiquing evidence

a. Students use a systematic method (e.g., a decision matrix) to identify the strengths and weaknesses of each solution. In their evaluation, students:

i. Evaluate each solution against each criterion and constraint.

ii. Compare solutions based on the results of their performance against the defined criteria and constraints.

b. Students use the evidence and reasoning to make a claim about the relative effectiveness of each proposed solution based on the strengths and weaknesses of each.

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.

Evidence Statements for MS-ETS1-3

1. Organizing data

a. Students organize given data (e.g., via tables, charts, or graphs) from tests intended to determine the effectiveness of three or more alternative solutions to a problem.

2. Identifying relationships

a. Students use appropriate analysis techniques (e.g., qualitative or quantitative analysis; basic statistical techniques of data and error analysis) to analyze the data and identify relationships within the datasets, including relationships between the design solutions and the given criteria and constraints.

3. Interpreting data

a. Students use the analyzed data to identify evidence of similarities and differences in features of the solutions.

b. Based on the analyzed data, students make a claim for which characteristics of each design best meet the given criteria and constraints.

c. Students use the analyzed data to identify the best features in each design that can be compiled into a new (improved) redesigned solution.

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.

Evidence Statements for MS-ETS1-4

1. Components of the model

a. Students develop a model in which they identify the components relevant to testing ideas about the designed system, including:

i. The given problem being solved, including criteria and constraints.

ii. The components of the given proposed solution (e.g., object, tools, or process), including inputs and outputs of the designed system.

2. Relationships

a. Students identify and describe* the relationships between components, including:

i. The relationships between each component of the proposed solution and the functionality of the solution.

ii. The relationship between the problem being solved and the proposed solution.

iii. The relationship between each of the components of the given proposed solution and the problem being solved.

iv. The relationship between the data generated by the model and the functioning of the proposed solution.

3. Connections

a. Students use the model to generate data representing the functioning of the given proposed solution and each of its iterations as components of the model are modified.

b. Students identify the limitations of the model with regards to representing the proposed solution.

c. Students describe* how the data generated by the model, along with criteria and constraints that the proposed solution must meet, can be used to optimize the design solution through iterative testing and modification