Background and context for the development of Mastery Based Learning

New Haven Public Schools has made a commitment to support the implementation of mastery- based learning as one component of personalizing learning. As part of this effort, the district has undertaken to define clear, common outcomes (core graduation competencies) for New Haven students. This clarity of outcomes further supports a portfolio of schools that offer varied paths to common learning outcomes. This small number of competencies will support the development and implementation of high quality curricula and assessments that will engage, support and measure deeper student learning. These core graduation competencies and performance indicators were created by using various CT and national standards. Great Schools Partnership is supporting New Haven Public Schools in the development of this work. While some individual schools were already working towards Mastery Based Learning, the district level work began in July of 2015 when a group of educators from several high schools in the district as well as those in district-level positions came together to create a draft set of common, Cross-Curricular Graduation Competencies. New Haven’s 21st century competencies were used as a starting point along with models and exemplars from other districts and states. In October 2015, the draft set of Cross-Curricular Graduation Competencies created by this working group was shared with a larger group of New Haven educators representing high schools across the district as well as the district office, and a second draft was created based on this feedback.

Beginning in December 2015, the Science Curriculum Facilitators and representatives from each mastery learning high school began work to develop Content Area Competencies and Performance Indicators aligned to both the vision of NHPS current science curriculum and future Next Generation Science Standards.. A revised draft of these Content Area Competencies and Performance Indicators is being presented to the district’s high school Science teachers for review and feedback during the March 21st CIA. This feedback will inform further revision of this draft. Following this, work will begin on scoring criteria rubric that can be used for each performance indicator.

Review of this draft should consider the following points: 1) Not everything that could be valuable for students can be included. Educators should differentiate between those standards they feel students must know versus standards that would be nice to know. These competencies and their performance indicators are focused on what every student must know.

2) These competencies and performance indicators will guide and shape the districts and schools’ curriculum and assessment practices. They need to be written in ways that are most helpful for developing and refining curriculum and assessment. On this last point, assessment should be considered broadly, specifically including performance assessments and various portfolios—not just paper and pencil tests.

3) It is important to note that aligning instructional and assessment practice to these competencies does not equate to a shift to mastery based grading. This small set of competencies is designed to focus and cohere our outcomes while enabling varied paths to achieve those outcomes. Decisions of how to report student learning, while related, will vary by school.

Based on meeting in January we came up with 9 (Questioning, Investigation, Models, Data, Claims/Explanations, Argument, Connections to Concepts, Communication, and possibly Engineering)

Feb meeting reduced these to 5 (with the question of Engineering as a sixth still open)

What might be now missing: engineering design process (problems instead of questions, design instead of investigate, solution instead of explanation/argument)

What’s redundant: Communication was decided that it is included under cross curricular (21st cent)Claims/explanations were combined with argument from evidence) as we know they are distinct but conclusions lead to claims lead to arguments in science, so we could combine.Connections to Cross Cutting Concepts was eliminated.

Science Graduation Competencies (draft)1.   Questioning:  Students can develop relevant scientific questions on their own to solve a problem or create an experiment.2. Investigations: Students can and conduct safe, skill-based investigations to demonstrate potential causal relationships. 3. Models: Students will construct, use and revise models to build scientific explanations and predict system outputs4. Data: Students will use a range of tools, technology and mathematical computation to analyze and interpret data.  5.  Claims & Argumentation: Students will be able to develop, evaluate, critique, and argue claims or solutions based on valid and reliable evidence from the natural and designed world.

** 6. ENGINEERING: Students will understand the interdependence of Science, Engineering, Technology and the influence of science, engineering and technology on the natural world and be able to apply the engineering design process to defining, developing and optimizing solutions to problems. (NGSS ETS)

Graduation Competency Science Performance Indicators (draft Mar 2016)1.   Questioning:  Students can develop relevant scientific questions on their own to solve a problem or create an experiment.

1. Ask specific questions from phenomena, unexpected results, and/or theories that arise.2. Ask (Construct) questions to clarify an explanation or a problem.3. Ask questions to determine relationships between an independent variable and dependent variable, that are testable with available resources.4. Ask (Construct) specific questions to refine a model.5. Ask specific questions to challenge the premise of an argument.6. Evaluate questions based on specificity, relevance, and test-ability.

2. Investigations: Students can and conduct safe, skill-based investigations to demonstrate potential causal relationships.

1. Formulate a testable hypothesis and demonstrate logical connections between the scientific concepts guiding the hypothesis and design of the experiment.

2. Plan an investigation and/or evaluate and/or revise the experimental design to produce data to serve as the basis for evidence that meets the goals of the investigation.

3. Understands that the design of the investigation and/or the accuracy of the data collection impacts the basis of evidence/strength of claim.4. Identify independent and dependent variables, including those that are kept constant and those used as controls.5. Appropriately uses tools (including industry-based lab equipment) and techniques to gather data and make observations.

3. Models: Students will construct, use and revise models to build scientific explanations and predict system outputs

1. Examine the scientific view of nature and reproduce phenomena through their own effort to understand how the world works(obtain information)

2. Propose a design for a model or functional device that uses qualitative and quantitative criteria (develop and use a model)3. Represent a system and interactions through inputs, outputs and processes (obtain data)4. Analyze and interpret data, using mathematics and computational thinking to adjust outcomes (analyze data)5. Construct an explanation for results and use evidence to support an argument (engage in argument)6. Understand that different models (such as thought processes, physical replicas, pictures, and analogies) can be used to represent the same thing. (understand argument)

7. Communicate explanations (for science) and design solutions (for engineering) (publish or show) to create a solution (solve a problem)8. Apply the use of technology and mathematics to inquiry learning practices (application/engineering)

4. Data: Students will use a range of tools, technology and mathematical computation to analyze and interpret data.

1. Analyze data using tools, technologies and/or models (e.g., computational mathematical) in order to make valid and reliable scientific claim.2. Apply concepts of statistics and probability including determining function fits to data, slope, intercept, and correlation coefficient for linear fits to scientific and engineering questions and problems, using digital tools when feasible.

3. Consider limitations of data analysis (e.g. measurement error, sample selection) when analyzing and interpreting data.4. Compare and contrast various types of data sets to examine consistency of measurements and observations.5. Apply techniques of algebra and functions to represent and solve scientific and engineering problems.6. Apply ratios, rates, percentages, and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units.

7. Use units as a way to understand problems and to guide solution of multi-step problems, choose and interpret the scale and the origin in graphs and data display.

8. Be able to represent data with plots on the real number line (dot plots, histograms, and box plots).9. Graph functions expressed symbolically and show key feature of graph by hand in simple cases and using technology for more complex cases.

5.  Claims & Argumentation: Students will be able to develop, evaluate, critique, and argue claims or solutions based on valid and reliable evidence from the natural and designed world.

1. Construct an explanation that includes quantitative or qualitative relationships between variables that predicts or describes phenomena.2. Take into account unanticipated effects in the development of evaluation, critique, and argumentation.3. Design, evaluate, and /or refine a solution to a complex, real-world problem while applying scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion.

4. Compare and critique two arguments on the same topic and analyze whether they emphasize similar or different evidence and/or interpretation of facts.

5. Construct, use, and/or present an oral and/or written argument supported by empirical evidence and scientific reasoning to support or refute an explanation/model for a phenomenon or a solution to a problem.

6. Evaluate competing design solutions based on design criteria.

Graduation Competency Performance Indicators1.   Questioning:  Students can develop relevant scientific questions on their own to solve a problem or create an experiment.

1. Ask specific questions from phenomena, unexpected results, and/or theories that arise.

2. Ask (Construct) questions to clarify an explanation or a problem.3. Ask questions to determine relationships between an independent variable and dependent variable, that are testable with available resources.

4. Ask (Construct) specific questions to refine a model.5. Ask specific questions to challenge the premise of an argument.6. Evaluate questions based on specificity, relevance, and test-ability.

D INQ.1 Identify questions that can be answered through scientific investigation.IDEAS FROM LARGE GROUP TO BE INCLUDED: Asks specific, relevant, and testable questions

IDEAS FROM NGSS PRACTICE 1 SUBTOPICS P1-1: Ask questions that arise from careful observation of phenomena, models, or unexpected results, to clarify and/or seek additional information. MS-P1-2: Ask questions to identify and/or clarify evidence and/or the premise(s) of an argument. HS-P1-2: Ask questions that arise from examining models or a theory, to clarify and/or seek additional information and relationships. MS-P1-3: Ask questions to determine relationships between independent and dependent variables and relationships in models. HS-P1-3: Ask questions to determine relationships, including quantitative relationships, between independent and dependent variables. P1-4: Ask questions to clarify and/or refine a model, an explanation, or an engineering problem. MS-P1-5: Ask questions that require sufficient and appropriate empirical evidence to answer. HS-P1-5: Evaluate a question to determine if it is testable and relevant. MS-P1-6: Ask questions that can be investigated within the scope of the classroom, outdoor environment, and museums and other public facilities with available resources and, when appropriate, frame a hypothesis based on observations and scientific principles HS-P1-6: Ask questions that can be investigated within the scope of the school laboratory, research facilities, or field (e.g., outdoor environment) with available resources and, when appropriate, frame a hypothesis based on a model or theory. MS-P1-7: Ask questions that challenge the premise(s) of an argument or the interpretation of a data set. HS-P1-7: Ask and/or evaluate questions that challenge the premise(s) of an argument, the interpretation of a data set, or the suitability of a design. MS-P1-8: Define a design problem that can be solved through the development of an object, tool, process or system and includes multiple criteria and constraints, including scientific knowledge that may limit possible solutions. HS-P1-8: Define a design problem that involves the development of a process or system with interacting components and criteria and constraints that may include social, technical, and/or environmental considerations. HS-P1-8: Analyze complex real-world problems by specifying criteria and constraints for successful solutions

2. Investigations: Students can and conduct safe, skill-based investigations to demonstrate potential causal relationships.

1. Formulate a testable hypothesis and demonstrate logical connections between the scientific concepts guiding the hypothesis and design of the experiment.

2. Plan an investigation and/or evaluate and/or revise the experimental design to produce data to serve as the basis for evidence that meets the goals of the investigation.

3. Understands that the design of the investigation and/or the accuracy of the data collection impacts the basis of evidence/strength of claim.

4. Identify independent and dependent variables, including those that are kept constant and those used as controls.

5. Appropriately uses tools (including industry-based lab equipment) and techniques to gather data and make observations.

IDEAS FROM LARGE GROUP TO BE INCLUDED?: Nature of Inquiry. Scientific method, Planning and carrying out investigations., Investigate potential causal relationships, Safety., Using Lab Equipment (Richard says industry/college wants this!)

CURRENT STATE STANDARDS: D INQ.3 Formulate a testable hypothesis and demonstrate logical connections between the scientific concepts guiding the hypothesis and the design of the experiment., D INQ.4 Design and conduct appropriate types of scientific investigations to answer different questions., D INQ.5 Identify independent and dependent variables, including those that are kept constant and those used as controls., D INQ.6 Use appropriate tools and techniques to make observations and gather data.

IDEAS FROM NGSS PRACTICE 2 SUBTOPICS MS-P3-1: 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. HS-P3-1: Plan an investigation or test a design individually and collaboratively to produce data to serve as the basis for evidence as part of building and revising models, supporting explanations for phenomena, or testing solutions to problems. Consider possible confounding variables or effects and evaluate the investigation’s design to ensure variables are controlled.

INVESTIGATIONS PAGE 2 MS-P3-2: 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. HS-P3-2: Plan and conduct an investigation individually and collaboratively to produce data to serve as the basis for evidence, and in the design: decide on types, how much, and accuracy of data needed to produce reliable measurements and consider limitations on the precision of the data (e.g., number of trials, cost, risk, time), and refine the design accordingly. MS-P3-3: Evaluate the accuracy of various methods for collecting data.HS-P3-3: Plan and conduct an investigation or test a design solution in a safe and ethical manner including considerations of environmental, social, and personal impacts. MS-P3-4: Collect data to produce data to serve as the basis for evidence to answer scientific questions or test design solutions under a range of conditions. HS-P3-4: Select appropriate tools to collect, record, analyze, and evaluate data. MS-P3-5: Collect data about the performance of a proposed object, tool, process or system under a range of conditions. HS-P3-5: Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.

IDEAS FROM NGSS NATURE OF SCIENCE•Science investigations use diverse methods and do not always use the same set of procedures to obtain data.

•New technologies advance scientific knowledge. •Scientific inquiry is characterized by a common set of values that include logical thinking, precision, open-mindedness, objectivity, skepticism, replicability of results, and honest and ethical reporting of findings. •The discourse practices of science are organized around disciplinary domains that share exemplars for making decisions regarding the values, instruments, methods, models, and evidence to adopt and use. •Scientific investigations use a variety of methods, tools, and techniques to revise and produce new knowledge.

3. Models: Students will construct, use and revise models to build scientific explanations and predict system outputs

1. Examine the scientific view of nature and reproduce phenomena through their own effort to understand how the world works (obtain information)

2. Propose a design for a model or functional device that uses qualitative and quantitative criteria (develop and use a model)

3. Represent a system and interactions through inputs, outputs and processes (obtain data)

4. Analyze and interpret data, using mathematics and computational thinking to adjust outcomes (analyze data)

5. Construct an explanation for results and use evidence to support an argument (engage in argument)

6. Understand that different models (such as though processes, physical replicas, pictures, and analogies) can be used to represent the same thing. (understand argument)

7. Communicate explanations (for science) and design solutions (for engineering) (publish or show) to create a solution (solve a problem)

8. Apply the use of technology and mathematics to inquiry learning practices (application/engineering)

IDEAS FROM LARGE GROUP TO BE INCLUDED:Investigate and analyze a natural human designed system in terms of its boundaries inputs, outputs, interactions & behaviors and use this info to develop a system model to predict its behavior

IDEAS FROM NGSS CROSS CUTTING CONCEPTS 4: Systems and System Models: MS-CCC4-1: Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy, matter, and information flows within systems. HS-CCC4-1: Models (e.g., physical, mathematical, computer models) can be used to simulate systems and interactions—including energy, matter, and information flows— within and between systems at different scales.

Systems and System Models: MS-CCC4-2: Systems may interact with other systems; they may have sub-systems and be a part of larger complex systems HS-CCC4-2: Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.

Systems and System Models: HS-CCC4-3: When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models.

MODELS PAGE 2 IDEAS FROM NGSS PRACTICE 2 MS-P2-1: Evaluate limitations of a model for a proposed object or tool. HS-P2-1: Evaluate merits and limitations of two different models of the same proposed tool, process, mechanism or system in order to select or revise a model that best fits the evidence or design criteria.

MS-P2-2: Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed. HS-P2-2: Design a test of a model to ascertain its reliability.

MS-P2-3: Use and/or develop a model of simple systems with uncertain and less predictable factors.HS-P2-3: Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system. (

MS-P2-4: Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena. HS-P2-4: Develop and/or use multiple types of models to provide mechanistic accounts and/or predict phenomena, and move flexibly between model types based on merits and limitations.

MS-P2-5: Develop and/or use a model to predict and/or describe phenomena. HS-P2-5: Develop a complex model that allows for manipulation and testing of a proposed process or system.

MS-P2-6: Develop a model to describe unobservable mechanisms. HS-P2-6: Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

MS-P2-7: 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.

4. Data: Students will use a range of tools, technology and mathematical computation to analyze and interpret data.

1. Analyze data using tools, technologies and/or models (e.g., computational mathematical) in order to make valid and reliable scientific claim.

2. Apply concepts of statistics and probability including determining function fits to data, slope, intercept, and correlation coefficient for linear fits to scientific and engineering questions and problems, using digital tools when feasible.

3. Consider limitations of data analysis (e.g. measurement error, sample selection) when analyzing and interpreting data.

4. Compare and contrast various types of data sets to examine consistency of measurements and observations.

5. Apply techniques of algebra and functions to represent and solve scientific and engineering problems.

6. Apply ratios, rates, percentages, and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units.

7. Use units as a way to understand problems and to guide solution of multi-step problems, choose and interpret the scale and the origin in graphs and data display.

8. Be able to represent data with plots on the real number line (dot plots, histograms, and box plots).

9. Graph functions expressed symbolically and show key feature of graph by hand in simple cases and using technology for more complex cases.

D INQ.8 Use mathematical operations to analyze and interpret data, and present relationships between variables in appropriate forms.D INQ.7 Assess the reliability of the data that was generated in the investigation.

IDEAS FROM LARGE GROUP TO BE INCLUDED:Recognize patterns in data and phenomena

IDEAS FROM NGSS CROSS CUTTING CONCEPTS: Patterns: MS-CCC1-2: Macroscopic patterns are related to the nature of microscopic and atomic-level structure. HS-CCC1-2: Empirical evidence is needed to identify patterns.

Patterns: MS-CCC1-1: Graphs, charts, and images can be used to identify patterns in data. HS-CCC1-1: Different patterns may be observed at each of the scales at which a system is studied and can provide evidence for causality in explanations of phenomena. Patterns: MS-CCC1-3: Patterns can be used to identify cause and effect relationships. Patterns: MS-CCC1-4: Patterns in rates of change and other numerical relationships can provide information about natural systems.

DATA PAGE 2 IDEAS FROM NGSS PRACTICES 4 & 5: MS-P4-1: Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.HS-P4-1: Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims MS-P4-2: Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.HS-P4-2: Apply concepts of statistics and probability (including determining function fits to data, slope, intercept, and correlation coefficient for linear fits) to scientific and engineering questions and problems, using digital tools when feasible MS-P4-3: Distinguish between causal and correlational relationships in data. HS-P4-3: Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data. MS-P4-4: Analyze and interpret data to provide evidence for phenomena. HS-P4-4: Compare and contrast various types of data sets to examine consistency of measurements and observations. MS-P4-5: Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible. MS-P4-6: 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 MS-P4-7: Analyze and interpret data to determine similarities and differences in findings. MS-P5-1: Use digital tools (e.g., computers) to analyze very large data sets for patterns and trends.HS-P5-1: Create and/or revise a computational model or simulation of a phenomenon, device, process, or system MS-P5-2: Use mathematical representations to describe and/or support scientific conclusions and design solutions. HS-P5-2: Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations MS-P5-3: Create algorithms (a series of ordered steps) to solve a problem. HS-P5-3: Apply techniques of algebra and functions to represent and solve scientific and engineering problems. MS-P5-4: Apply mathematical concepts and/or processes to scientific and engineering questions and problems. HS-P5-4: Use simple limit cases to test mathematical expressions, computer programs, algorithms, or simulations of a process or system to see if a model “makes sense” by comparing the outcomes with what is known about the real world. HS-P5-5: Apply ratios, rates, percentages, and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units .

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5.  Claims & Argumentation: Students will be able to develop, evaluate, critique, and argue claims or solutions based on valid and reliable evidence from the natural and designed world.

1. Construct an explanation that includes quantitative or qualitative relationships between variables that predicts or describes phenomena.

2. Take into account unanticipated effects in the development of evaluation, critique, and argumentation.

3. Design, evaluate, and /or refine a solution to a complex, real-world problem while applying scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion.

4. Compare and critique two arguments on the same topic and analyze whether they emphasize similar or different evidence and/or interpretation of facts.

5. Construct, use, and/or present an oral and/or written argument supported by empirical evidence and scientific reasoning to support or refute an explanation/model for a phenomenon or a solution to a problem.

6. Evaluate competing design solutions based on design criteria.

Students will develop and evaluate claims and/or solutions based on valid and reliable evidence consistent with scientific ideas, principles, and theories. D INQ.2 Read, interpret, examine the credibility and validity of scientific claims in different sources of information.D INQ.9 Articulate conclusions and explanations based on research data, and assess results based on the design of the investigation.

IDEAS FROM LARGE GROUP TO BE INCLUDEDAnalyze credibility and reliability of sources , The analysis and application of science literature to support a claim (explanation), Evidence – use information to draw relevant, reasonable, thorough conclusions .IDEAS FROM NGSS PRACTICE 6 MS-P6-1: Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena. HS-P6-1: Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables. MS-P6-2: Construct an explanation using models or representations. HS-P6-2: Construct and revise an explanation based on valid and reliable evidence obtained from a variety of sources (including students’ own investigations, models, theories, simulations, peer review) and the assumption that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future MS-P6-3: Construct a scientific explanation based on valid and reliable evidence obtained from sources (including the students’ own experiments) and the assumption that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future. HS-P6-3: Apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena and solve design problems, taking into account possible unanticipated effects.

MS-P6-4: Apply scientific ideas, principles, and/or evidence to construct, revise and/or use an explanation for real-world phenomena, examples, or events.HS-P6-4: Apply scientific reasoning, theory, and/or models to link evidence to the claims to assess the extent to which the reasoning and data support the explanation or conclusion CLAIMS & ARGUMENTATION PAGE 2 MS-P6-5: Apply scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion. HS-P6-5: Design, evaluate, and/or refine a solution to a complex real-world problem, based on scientific knowledge, student-generated sources of evidence, prioritized criteria, and tradeoff considerations.

Argument: Students can engage in argument from evidence using appropriate and sufficient evidence and scientific reasoning to defend and critique claims and explanations about the natural and designed world.

D INQ.9 Articulate conclusions and explanations based on research data, and assess results based on the design of the investigation.

IDEAS FROM NGSS PRACTICE 7 SUB TOPICSMS-P7-1: Compare and critique two arguments on the same topic and analyze whether they emphasize similar or different evidence and/or interpretations of facts. HS-P7-1: Compare and evaluate competing arguments or design solutions in light of currently accepted explanations, new evidence, limitations (e.g., trade-offs), constraints, and ethical issues.

MS-P7-2: Respectfully provide and receive critiques about one’s explanations, procedures, models, and questions by citing relevant evidence and posing and responding to questions that elicit pertinent elaboration and detail. HS-P7-2: Evaluate the claims, evidence, and/or reasoning behind currently accepted explanations or solutions to determine the merits of arguments

MS-P7-3: 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. HS-P7-3: Respectfully provide and/or receive critiques on scientific arguments by probing reasoning and evidence, challenging ideas and conclusions, responding thoughtfully to diverse perspectives, and determining additional information required to resolve contradictions.

MS-P7-4: Make an oral or written argument that supports or refutes the advertised performance of a device, process, or system based on empirical evidence concerning whether or not the technology meets relevant criteria and constraints.HS-P7-4: Construct, use, and/or present an oral and written argument or counter-arguments based on data and evidence.

MS-P7-5: Evaluate competing design solutions based on jointly developed and agreed-upon design criteria. HS-P7-5: Make and defend a claim based on evidence about the natural world or the effectiveness of a design solution that reflects scientific knowledge and student-generated evidence.

HS-P7-6: Evaluate competing design solutions to a real-world problem based on empirical evidence, and/or logical arguments regarding relevant factors (e.g. economic, societal, environmental, ethical considerations).

6. ENGINEERING: Students will understand the interdependence of Science, Engineering, Technology and the influence of science, engineering and technology on the natural world and be able to apply the engineering design process to defining, developing and optimizing solutions to problems.

IDEAS FROM MBA:. Students design, create, and build a model or functional device (physical or digital) that supports the engineering standards.

HS-ETS1-1. Analyze a major global challenge to specify qualitative and quantitative criteria and constraints for solutions that account for societal needs and wants. ETS1.A. Defining and Delimiting Engineering ProblemsCriteria and constraints also include satisfying any requirements set by society, such as taking issues of risk mitigation into account, and they should be quantified to the extent possible and stated in such a way that one can tell if a given design meets them. Humanity faces major global challenges today, suchas the need for supplies of clean water and food or for energy sources that minimize pollution, which can be addressed through engineering. These global challenges also may have manifestations in local communities.

HS-ETS1-2. Design a solution to a complex real- world problem by breaking it down into smaller, more manageable problems that can be solved through engineering. ETS1.C. Optimizing the Design Solution Criteria may need to be broken down into simpler ones that can be approached systematically, and decisions about the priority of certain criteria over others (trade- offs) may be needed.

HS-ETS1-3. Evaluate a solution to a complex real-world problem based on prioritized criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics as well as possible social, cultural, and environmental impacts. ETS1.B. Developing Possible Solutions When evaluating solutions it is important to take into account a range of constraints including cost, safety, reliability, and aesthetics and to consider social, cultural, and environmental impacts.

HS-ETS1-4. Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem. ETS1.B. Developing Possible Solutions Both physical models and computers can be used in various ways to aid in the engineering design process. Computers are useful for a variety of purposes, such as running simulations to test different ways of solving a problem or to see which one is most efficient or economical, and in making a persuasive presentation to a client about how a given design will meet his or her needs.