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APPENDIX F can use their understanding to investigate the natural world through the practices of science inquiry, and can solve meaning- SCIENCE AND ENGINEERING PRACTICES ful problems through the practices of engineering design. The IN THE NEXT GENERATION SCIENCE Framework uses the term “practices,” rather than “science pro- STANDARDS cesses” or “inquiry” skills, for a specific reason: We use the term “practices” instead of a term such as “skills” to emphasize that engaging in scientific investi- gation requires not only skill but also knowledge that is specific to each practice. (NRC, 2012, p. 30) A Framework for K–12 Science Education (Framework) provides the blueprint for developing the Next Generation Science Standards The eight practices of science and engineering that the (NGSS). The Framework expresses a vision in science education that Framework identifies as essential for all students to learn, and requires students to operate at the nexus of three dimensions of describes in detail, are listed below: learning: Science and Engineering Practices, Disciplinary Core Ideas, 1. Asking questions (for science) and defining problems (for and Crosscutting Concepts. The Framework identified a small num- engineering) ber of disciplinary core ideas that all students should learn with 2. Developing and using models increasing depth and sophistication, from kindergarten through 3. Planning and carrying out investigations twelfth grade. Key to the vision expressed in the Framework is for 4. Analyzing and interpreting data students to learn these disciplinary core ideas in the context of sci- 5. Using mathematics and computational thinking ence and engineering practices. The importance of combining sci- 6. Constructing explanations (for science) and designing solutions ence and engineering practices and disciplinary core ideas is stated (for engineering) in the Framework as follows: 7. Engaging in argument from evidence Standards and performance expectations that are aligned 8. Obtaining, evaluating, and communicating information to the framework must take into account that students cannot fully understand scientific and engineering ideas RATIONALE without engaging in the practices of inquiry and the dis- courses by which such ideas are developed and refined. At Chapter 3 of the Framework describes each of the eight practices the same time, they cannot learn or show competence in of science and engineering and presents the following rationale practices except in the context of specific content. (NRC, for why they are essential: 2012, p. 218) Engaging in the practices of science helps students under- The Framework specifies that each performance expectation must stand how scientific knowledge develops; such direct combine a relevant practice of science or engineering, with a involvement gives them an appreciation of the wide core disciplinary idea and crosscutting concept, appropriate for range of approaches that are used to investigate, model, students of the designated grade level. That guideline is perhaps and explain the world. Engaging in the practices of engi- the most significant way in which the NGSS differs from prior neering likewise helps students understand the work of standards documents. In the future, science assessments will not engineers, as well as the links between engineering and assess students’ understanding of core ideas separately from their science. Participation in these practices also helps students abilities to use the practices of science and engineering. These form an understanding of the crosscutting concepts and two dimensions of learning will be assessed together, showing disciplinary ideas of science and engineering; moreover, students not only “know” science concepts, but also that students 48

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it makes students’ knowledge more meaningful and Students in grades K–12 should engage in all eight embeds it more deeply into their worldview. practices over each grade band. All eight practices are The actual doing of science or engineering can also pique accessible at some level to young children; students’ students’ curiosity, capture their interest, and motivate abilities to use the practices grow over time. However, their continued study; the insights thus gained help them the NGSS only identify the capabilities that students are recognize that the work of scientists and engineers is a expected to acquire by the end of each grade band (K–2, creative endeavor—one that has deeply affected the 3–5, 6–8, and 9–12). Curriculum developers and teachers world they live in. Students may then recognize that determine strategies that advance students’ abilities to science and engineering can contribute to meeting use the practices. many of the major challenges that confront society Practices grow in complexity and sophistication across today, such as generating sufficient energy, preventing the grades. The Framework suggests how students’ capa- and treating disease, maintaining supplies of fresh water bilities to use each of the practices should progress as they and food, and addressing climate change. mature and engage in science learning. For example, the Any education that focuses predominantly on the detailed practice of “planning and carrying out investigations” products of scientific labor—the facts of science—without begins at the kindergarten level with guided situations in developing an understanding of how those facts were which students have assistance in identifying phenomena established or that ignores the many important applica- to be investigated and how to observe, measure, and tions of science in the world misrepresents science and record outcomes. By upper elementary school, students marginalizes the importance of engineering. (NRC, 2012, should be able to plan their own investigations. The pp. 42–43) nature of investigations that students should be able to plan and carry out is also expected to increase as students As suggested in the rationale above, Chapter 3 derives the eight mature, including the complexity of questions to be practices based on an analysis of what professional scientists and studied; the ability to determine what kind of investiga- engineers do. It is recommended that users of the NGSS read that tion is needed to answer different kinds of questions; chapter carefully, as it provides valuable insights into the nature whether or not variables need to be controlled and if so, of science and engineering, as well as the connections between which are most important; and at the high school level, these two closely allied fields. The intent of this section of the how to take measurement error into account. As listed NGSS appendixes is more limited—to describe what each of these in the tables in this chapter, each of the eight practices eight practices implies about what students can do. Its purpose is has its own progression, from kindergarten to grade 12. to enable readers to better understand the performance expec- While these progressions are derived from Chapter 3 of tations. A “practices matrix” is included, which lists the specific the Framework, they are refined based on experiences in capabilities included in each practice for each grade band (K–2, crafting the NGSS and feedback received from reviewers. 3–5, 6–8, 9–12). Each practice may reflect science or engineering. Each of the eight practices can be used in the service of scientific GUIDING PRINCIPLES inquiry or engineering design. The best way to ensure a practice is being used for science or engineering is to ask The development process of the standards provided insights into about the goal of the activity. Is the goal to answer a science and engineering practices. These insights are shared in the question? If so, students are doing science. Is the purpose following guiding principles: to define and solve a problem? If so, students are doing engineering. Box 3-2 in Framework provides a side-by-side Science and Engineering Practices in the Next Generation Science Standards 49

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comparison of how scientists and engineers use these prac- practice. The most appropriate aspect of the practice is tices. This chapter briefly summarizes what it “looks like” for identified for each performance expectation. a student to use each practice for science or engineering. Engagement in practices is language intensive and Practices represent what students are expected to do and requires students to participate in classroom science are not teaching methods or curriculum. The Framework discourse. The practices offer rich opportunities and occasionally offers suggestions for instruction, such as how demands for language learning while advancing science a science unit might begin with a scientific investigation, learning for all students (Lee et al., in press). English which then leads to the solution of an engineering prob- language learners, students with disabilities that involve lem. The NGSS avoid such suggestions because the goal is language processing, students with limited literacy devel- to describe what students should be able to do, rather than opment, and students who are speakers of social or how they should be taught. For example, it was suggested regional varieties of English that are generally referred that the NGSS to recommend certain teaching strategies to as “non-standard English” stand to gain from science such as using biomimicry—the application of biological learning that involves language-intensive scientific and features to solve engineering design problems. Although engineering practices. When supported appropriately, instructional units that make use of biomimicry seem well these students are capable of learning science through aligned with the spirit of the Framework to encourage their emerging language and of comprehending and car- integration of core ideas and practices, biomimicry and rying out sophisticated language functions (e.g., arguing similar teaching approaches are more closely related to from evidence, providing explanations, developing mod- curriculum and instruction than to assessment. Hence, the els) using less-than-perfect English. By engaging in such decision was made not to include biomimicry in the NGSS. practices, moreover, they simultaneously build on their The eight practices are not separate; they intentionally understanding of science and their language proficiency overlap and interconnect. As explained by Bell et al. (2012), (i.e., capacity to do more with language). the eight practices do not operate in isolation. Rather, they On the following pages, each of the eight practices is briefly tend to unfold sequentially, and even overlap. For example, described. Each description ends with a table illustrating the com- the practice of “asking questions” may lead to the practice ponents of the practice that students are expected to master at of “modeling” or “planning and carrying out an investiga- the end of each grade band. All eight tables comprise the practices tion,” which in turn may lead to “analyzing and interpret- matrix. During development of the NGSS, the practices matrix was ing data.” The practice of “mathematical and computa- revised several times to reflect improved understanding of how tional thinking” may include some aspects of “analyzing the practices connect with the disciplinary core ideas. and interpreting data.” Just as it is important for students to carry out each of the individual practices, it is important for them to see the connections among the eight practices. PRACTICE 1: ASKING QUESTIONS AND DEFINING PROBLEMS Performance expectations focus on some but not all capabilities associated with a practice. The Framework Students at any grade level should be able to ask questions identifies a number of features or components of each of each other about the texts they read, the features of the practice. The practices matrix described in this section lists phenomena they observe, and the conclusions they draw the components of each practice as a bulleted list within from their models or scientific investigations. For engineer- each grade band. As the performance expectations were ing, they should ask questions to define the problem to be developed, it became clear that it is too much to expect solved and to elicit ideas that lead to the constraints and each performance to reflect all components of a given specifications for its solution. (NRC, 2012, p. 56) 50 NEXT GENERATION SCIENCE STANDARDS

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Practice 1: Asking Questions and Defining Problems Grades K–2 Grades 3–5 Grades 6–8 Grades 9–12 Asking questions and defining problems Asking questions and defining problems Asking questions and defining problems Asking questions and defining problems in K–2 builds on prior experiences in 3–5 builds on K–2 experiences and in 6–8 builds on K–5 experiences and in 9–12 builds on K–8 experiences and and progresses to simple descriptive progresses to specifying qualitative progresses to specifying relationships progresses to formulating, refining, and questions that can be tested. relationships. between variables and clarifying evaluating empirically testable questions •  sk questions based on observations A •  sk questions about what would A arguments and models. and design problems using models and to find more information about the happen if a variable is changed. •  sk questions A simulations. natural and/or designed world(s). • dentify scientific (testable) and non- I o  that arise from careful observation •  sk questions A •  sk and/or identify questions that can A scientific (non-testable) questions. of phenomena, models, or o  that arise from careful observation of be answered by an investigation. •  sk questions that can be investigated A unexpected results, to clarify and/or phenomena, or unexpected results, •  efine a simple problem that can be D and predict reasonable outcomes seek additional information. to clarify and/or seek additional solved through the development of a based on patterns such as cause and o  identify and/or clarify evidence to information. new or improved object or tool. effect relationships. and/or the premise(s) of an o  that arise from examining models •  se prior knowledge to describe U argument. or a theory, to clarify and/or problems that can be solved. o  determine relationships between to seek additional information and •  efine a simple design problem D independent and dependent relationships. that can be solved through the variables and relationships in o  determine relationships, including to development of an object, tool, models. quantitative relationships, between process, or system and includes o  clarify and/or refine a model, to independent and dependent variables. several criteria for success and an explanation, or an engineering o  clarify and refine a model, an to constraints on materials, time, or cost. problem. explanation, or an engineering o  that require sufficient and problem. appropriate empirical evidence to •  valuate a question to determine if it is E answer. testable and relevant. o  that can be investigated within the •  sk questions that can be investigated A scope of the classroom, outdoor within the scope of the school laboratory, environment, and museums and research facilities, or field (e.g., outdoor other public facilities with available environment) with available resources resources and, when appropriate, and, when appropriate, frame a frame a hypothesis based on hypothesis based on a model or theory. observations and scientific •  sk and/or evaluate questions that A principles. challenge the premise(s) of an argument, o  that challenge the premise(s) of an the interpretation of a data set, or the argument or the interpretation of a suitability of a design. data set. •  efine a design problem that involves D •  efine a design problem that can be D the development of a process or system solved through the development of with interacting components and an object, tool, process, or system criteria and constraints that may include and includes multiple criteria and social, technical, and/or environmental constraints, including scientific considerations. knowledge that may limit possible solutions. Science and Engineering Practices in the Next Generation Science Standards 51

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Scientific questions arise in a variety of ways. They can be driven PRACTICE 2: DEVELOPING AND USING MODELS by curiosity about the world, inspired by the predictions of a model, theory, or findings from previous investigations, or they Modeling can begin in the earliest grades, with students’ can be stimulated by the need to solve a problem. Scientific ques- models progressing from concrete “pictures” and/or tions are distinguished from other types of questions in that the physical scale models (e.g., a toy car) to more abstract rep- answers lie in explanations supported by empirical evidence, resentations of relevant relationships in later grades, such including evidence gathered by others or through investigation. as a diagram representing forces on a particular object in While science begins with questions, engineering begins with a system. (NRC, 2012, p. 58) defining a problem to solve. However, engineering may also Models include diagrams, physical replicas, mathematical repre- involve asking questions to define a problem, such as: What is the sentations, analogies, and computer simulations. Although models need or desire that underlies the problem? What are the criteria do not correspond exactly to the real world, they bring certain for a successful solution? Other questions arise when generating features into focus while obscuring others. All models contain ideas, or testing possible solutions, such as: What are the possible approximations and assumptions that limit the range of validity tradeoffs? What evidence is necessary to determine which solu- and predictive power, so it is important for students to recognize tion is best? their limitations. Asking questions and defining problems also involves asking ques- In science, models are used to represent a system (or parts of tions about data, claims that are made, and proposed designs. It is a system) under study, to aid in the development of questions important to realize that asking a question also leads to involve- and explanations, to generate data that can be used to make ment in another practice. A student can ask a question about data predictions, and to communicate ideas to others. Students can that will lead to further analysis and interpretation. Or a student be expected to evaluate and refine models through an itera- might ask a question that leads to planning and design, an inves- tive cycle of comparing their predictions with the real world and tigation, or the refinement of a design. then adjusting them to gain insights into the phenomenon being Whether engaged in science or engineering, the ability to ask modeled. As such, models are based on evidence. When new evi- good questions and clearly define problems is essential for every- dence is uncovered that the models cannot explain, models are one. The following progression of Practice 1 summarizes what modified. students should be able to do by the end of each grade band. In engineering, models may be used to analyze a system to see Each of the examples of asking questions below leads to students where or under what conditions flaws might develop or to test engaging in other scientific practices. possible solutions to a problem. Models can also be used to visu- alize and refine a design, to communicate a design’s features to others, and as prototypes for testing design performance. 52 NEXT GENERATION SCIENCE STANDARDS

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Practice 2: Developing and Using Models Grades K–2 Grades 3–5 Grades 6–8 Grades 9–12 Modeling in K–2 builds on prior Modeling in 3–5 builds on K–2 Modeling in 6–8 builds on K–5 Modeling in 9–12 builds on K–8 experiences experiences and progresses to include experiences and progresses to building experiences and progresses to and progresses to using, synthesizing, and using and developing models (i.e., and revising simple models and using developing, using, and revising models to developing models to predict and show diagram, drawing, physical replica, models to represent events and design describe, test, and predict more abstract relationships among variables between diorama, dramatization, or storyboard) solutions. phenomena and design systems. systems and their components in the natural that represent concrete events or design • dentify limitations of models. I •  valuate limitations of a model for a E and designed world(s). solutions. •  ollaboratively develop and/or C proposed object or tool. •  valuate merits and limitations of two E •  istinguish between a model and the D revise a model based on evidence •  evelop or modify a model—based on D different models of the same proposed actual object, process, and/or events that shows the relationships among evidence—to match what happens if tool, process, mechanism, or system in the model represents. variables for frequent and regular a variable or component of a system is order to select or revise a model that best •  ompare models to identify common C occurring events. changed. fits the evidence or design criteria. features and differences. •  evelop a model using an analogy, D •  se and/or develop a model of simple U •  esign a test of a model to ascertain its D •  evelop and/or use a model to D example, or abstract representation to systems with uncertain and less reliability. represent amounts, relationships, describe a scientific principle or design predictable factors. •  evelop, revise, and/or use a model based D relative scales (bigger, smaller), and/or solution. •  evelop and/or revise a model D on evidence to illustrate and/or predict the patterns in the natural and designed •  evelop and/or use models to describe D to show the relationships among relationships between systems or between world(s). and/or predict phenomena. variables, including those that are components of a system. •  evelop a simple model based on D •  evelop a diagram or simple physical D not observable but predict observable •  evelop and/or use multiple types of D evidence to represent a proposed prototype to convey a proposed phenomena. models to provide mechanistic accounts object or tool. object, tool, or process. •  evelop and/or use a model to predict D and/or predict phenomena, and move •  se a model to test cause and U and/or describe phenomena. flexibly between model types based on effect relationships or interactions •  evelop a model to describe D merits and limitations. concerning the functioning of a unobservable mechanisms. •  evelop a complex model that allows for D natural or designed system. •  evelop and/or use a model to D manipulation and testing of a proposed generate data to test ideas about process or system. phenomena in natural or designed •  evelop and/or use a model (including D systems, including those representing mathematical and computational) to inputs and outputs and those at generate data to support explanations, unobservable scales. predict phenomena, analyze systems, and/ or solve problems. Science and Engineering Practices in the Next Generation Science Standards 53

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PRACTICE 3: PLANNING AND CARRYING OUT outcomes, and plan a course of action that will provide the best INVESTIGATIONS evidence to support their conclusions. Students should design investigations that generate data to provide evidence to support Students should have opportunities to plan and carry out claims they make about phenomena. Data are not evidence until several different kinds of investigations during their K–12 used in the process of supporting a claim. Students should use years. At all levels, they should engage in investigations reasoning and scientific ideas, principles, and theories to show that range from those structured by the teacher—in order why data can be considered evidence. to expose an issue or question that they would be unlikely Over time, students are expected to become more systematic and to explore on their own (e.g., measuring specific proper- careful in their methods. In laboratory experiments, students are ties of materials)—to those that emerge from students’ expected to decide which variables should be treated as results own questions. (NRC, 2012, p. 61) or outputs, which should be treated as inputs and intentionally Scientific investigations may be undertaken to describe a phenom- varied from trial to trial, and which should be controlled, or kept enon or to test a theory or model for how the world works. The the same across trials. In the case of field observations, planning purpose of engineering investigations might be to find out how involves deciding how to collect different samples of data under to fix or improve the functioning of a technological system or to different conditions, even though not all conditions are under the compare different solutions to see which best solves a problem. direct control of the investigator. Planning and carrying out inves- Whether students are doing science or engineering, it is always tigations may include elements of all of the other practices. important for them to state the goal of an investigation, predict 54 NEXT GENERATION SCIENCE STANDARDS

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Practice 3: Planning and Carrying Out Investigations Grades K–2 Grades 3–5 Grades 6–8 Grades 9–12 Planning and carrying out investigations Planning and carrying out investigations Planning and carrying out investigations Planning and carrying out investigations to answer questions or test solutions to answer questions or test solutions in 6–8 builds on K–5 experiences and in 9–12 builds on K–8 experiences and to problems in K–2 builds on prior to problems in 3–5 builds on K–2 progresses to include investigations progresses to include investigations that experiences and progresses to simple experiences and progresses to include that use multiple variables and provide provide evidence for and test conceptual, investigations, based on fair tests, which investigations that control variables and evidence to support explanations or mathematical, physical, and empirical provide data to support explanations or provide evidence to support explanations solutions. models. design solutions. or design solutions. •  lan an investigation individually P •  lan an investigation or test a design P •  ith guidance, plan and conduct an W •  lan and conduct an investigation P and collaboratively, and in the design individually and collaboratively to produce investigation in collaboration with collaboratively to produce data to identify independent and dependent data to serve as the basis for evidence peers (for K). serve as the basis for evidence, using variables and controls, what tools as part of building and revising models, •  lan and conduct an investigation P fair tests in which variables are are needed to do the gathering, how supporting explanations for phenomena, collaboratively to produce data to controlled and the number of trials is measurements will be recorded, and or testing solutions to problems. Consider serve as the basis for evidence to considered. how many data are needed to support possible confounding variables or effects answer a question. •  valuate appropriate methods and/or E a claim. and evaluate the investigation’s design to •  valuate different ways of observing E tools for collecting data. •  onduct an investigation and/ C ensure variables are controlled. and/or measuring a phenomenon to •  ake observations and/or M or evaluate and/or revise the •  lan and conduct an investigation P determine which way can answer a measurements to produce data to experimental design to produce data individually and collaboratively to produce question. serve as the basis for evidence for an to serve as the basis for evidence that data to serve as the basis for evidence, •  ake observations (firsthand or from M explanation of a phenomenon or to meet the goals of the investigation. and in the design decide on types, how media) and/or measurements to test a design solution. •  valuate the accuracy of various E much, and accuracy of data needed to collect data that can be used to make •  ake predictions about what would M methods for collecting data. produce reliable measurements and comparisons. happen if a variable changes. •  ollect data to produce data to serve C consider limitations on the precision of •  ake observations (firsthand or from M •  est two different models of the same T as the basis for evidence to answer the data (e.g., number of trials, cost, risk, media) and/or measurements of a proposed object, tool, or process to scientific questions or to test design time), and refine the design accordingly. proposed object, tool, or solution to determine which better meets criteria solutions under a range of conditions. •  lan and conduct an investigation or P determine if it solves a problem or for success. •  ollect data about the performance C test a design solution in a safe and meets a goal. of a proposed object, tool, process, or ethical manner, including considerations •  ake predictions based on prior M system under a range of conditions. of environmental, social, and personal experiences. impacts. •  elect appropriate tools to collect, record, S analyze, and evaluate data. •  ake directional hypotheses that M specify what happens to a dependent variable when an independent variable is manipulated. •  anipulate variables and collect data M about a complex model of a proposed process or system to identify failure points or improve performance relative to criteria for success or other variables. Science and Engineering Practices in the Next Generation Science Standards 55

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PRACTICE 4: ANALYZING AND As students mature, they are expected to expand their capabilities INTERPRETING DATA to use a range of tools for tabulation, graphical representation, visualization, and statistical analysis. Students are also expected to Once collected, data must be presented in a form that improve their abilities to interpret data by identifying significant can reveal any patterns and relationships and that allows features and patterns, use mathematics to represent relationships results to be communicated to others. Because raw data between variables, and take into account sources of error. When as such have little meaning, a major practice of scientists possible and feasible, students should use digital tools to analyze is to organize and interpret data through tabulating, and interpret data. Whether analyzing data for the purpose of graphing, or statistical analysis. Such analysis can bring science or engineering, it is important that students present data out the meaning of data—and their relevance—so that as evidence to support their conclusions. they may be used as evidence. Engineers, too, make decisions based on evidence that a given design will work; they rarely rely on trial and error. Engineers often analyze a design by creating a model or prototype and collecting extensive data on how it per- forms, including under extreme conditions. Analysis of this kind of data not only informs design decisions and enables the prediction or assessment of performance but also helps define or clarify problems, determine economic feasibility, evaluate alternatives, and investigate failures. (NRC, 2012, pp. 61–62) 56 NEXT GENERATION SCIENCE STANDARDS

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Practice 4: Analyzing and Interpreting Data Grades K–2 Grades 3–5 Grades 6–8 Grades 9–12 Analyzing data in K–2 builds on prior Analyzing data in 3–5 builds on Analyzing data in 6–8 builds on K–5 Analyzing data in 9–12 builds on K–8 experiences and progresses to collecting, K–2 experiences and progresses to experiences and progresses to extending experiences and progresses to introducing recording, and sharing observations. introducing quantitative approaches to quantitative analysis to investigations, more detailed statistical analysis, the •  ecord information (observations, R collecting data and conducting multiple distinguishing between correlation comparison of data sets for consistency, and thoughts, and ideas). trials of qualitative observations. When and causation, and basic statistical the use of models to generate and analyze •  se and share pictures, drawings, and/ U possible and feasible, digital tools should techniques of data and error analysis. data. or writings of observations. be used. •  onstruct, analyze, and/or interpret C •  nalyze data using tools, technologies, A •  se observations (firsthand or from U •  epresent data in tables and/ R graphical displays of data and/or and/or models (e.g., computational, media) to describe patterns and/ or various graphical displays (bar large data sets to identify linear and mathematical) in order to make valid and or relationships in the natural graphs, pictographs, and/or pie charts) non-linear relationships. reliable scientific claims or determine an and designed world(s) in order to to reveal patterns that indicate •  se graphical displays (e.g., maps, U optimal design solution. answer scientific questions and solve relationships. charts, graphs, and/or tables) of large •  pply concepts of statistics and probability A problems. •  nalyze and interpret data to make A data sets to identify temporal and (including determining function fits to data, •  ompare predictions (based on C sense of phenomena, using logical spatial relationships. slope, intercept, and correlation coefficient prior experiences) to what occurred reasoning, mathematics, and/or •  istinguish between causal and D for linear fits) to scientific and engineering (observable events). computation. correlational relationships in data. questions and problems, using digital tools •  nalyze data from tests of an object A •  ompare and contrast data collected C •  nalyze and interpret data to provide A when feasible. or tool to determine if it works as by different groups in order to discuss evidence for phenomena. •  onsider limitations of data analysis (e.g., C intended. similarities and differences in their •  pply concepts of statistics and A measurement error, sample selection) when findings. probability (including mean, median, analyzing and interpreting data. •  nalyze data to refine a problem A mode, and variability) to analyze and •  ompare and contrast various types of C statement or the design of a proposed characterize data, using digital tools data sets (e.g., self-generated, archival) to object, tool, or process. when feasible. examine consistency of measurements and •  se data to evaluate and refine design U •  onsider limitations of data analysis C observations. solutions. (e.g., measurement error) and/or seek •  valuate the impact of new data on a E to improve precision and accuracy of working explanation and/or model of a data with better technological tools proposed process or system. and methods (e.g., multiple trials). •  nalyze data to identify design features A •  nalyze and interpret data to A or characteristics of the components of a determine similarities and differences proposed process or system to optimize it in findings. relative to criteria for success. •  nalyze data to define an optimal A operational range for a proposed object, tool, process, or system that best meets criteria for success. Science and Engineering Practices in the Next Generation Science Standards 57

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PRACTICE 5: USING MATHEMATICS AND calculus. Computers and digital tools can enhance the power COMPUTATIONAL THINKING of mathematics by automating calculations, approximating solutions to problems that cannot be calculated precisely, and Although there are differences in how mathematics and analyzing large data sets available to identify meaningful pat- computational thinking are applied in science and in terns. Students are expected to use laboratory tools connected engineering, mathematics often brings these two fields to computers for observing, measuring, recording, and process- together by enabling engineers to apply the mathemati- ing data. Students are also expected to engage in computational cal form of scientific theories and by enabling scientists to thinking, which involves strategies for organizing and search- use powerful information technologies designed by engi- ing data, creating sequences of steps called algorithms, and neers. Both kinds of professionals can thereby accomplish using and developing new simulations of natural and designed investigations and analyses and build complex models, systems. Mathematics is a tool that is key to understanding sci- which might otherwise be out of the question. (NRC, ence. As such, classroom instruction must include critical skills 2012, p. 65) of mathematics. The NGSS display many of those skills through the performance expectations, but classroom instruction should Students are expected to use mathematics to represent physical enhance all of science through the use of quality mathematical variables and their relationships and to make quantitative pre- and computational thinking. dictions. Other applications of mathematics in science and engi- neering include logic, geometry, and at the highest levels, 58 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Asking Questions and • Define a simple problem that • Use prior knowledge to • Define a design problem that • Define a design problem that Defining Problems can be solved through the describe problems that can be can be solved through the involves the development development of a new or solved. development of an object, of a process or system with (continued) improved object or tool. • Define a simple design problem tool, process, or system and interacting components and that can be solved through the includes multiple criteria and criteria and constraints that development of an object, tool, constraints, including scientific may include social, technical, process, or system and includes knowledge that may limit and/or environmental several criteria for success and possible solutions. considerations. constraints on materials, time, or cost. Developing and Using Modeling in K–2 builds on prior Modeling in 3–5 builds on K–2 Modeling in 6–8 builds on K–5 Modeling in 9–12 builds on K–8 Models experiences and progresses to experiences and progresses to experiences and progresses to experiences and progresses to include using and developing building and revising simple developing, using, and revising using, synthesizing, and developing models (i.e., diagram, drawing, models and using models to models to describe, test, and models to predict and show A practice of both science physical replica, diorama, represent events and design predict more abstract phenomena relationships among variables dramatization, or storyboard) solutions. and design systems. between systems and their and engineering is to use that represent concrete events or components in the natural and and construct models as design solutions. designed world(s). helpful tools for representing ideas and explanations. • Distinguish between a model • Identify limitations of models. • Evaluate limitations of a model • Evaluate merits and limitations These tools include and the actual object, process, for a proposed object or tool. of two different models of the diagrams, drawings, physical and/or events the model same proposed tool, process, represents. mechanism, or system in order replicas, mathematical • Compare models to identify to select or revise a model that representations, analogies, common features and best fits the evidence or design and computer simulations. differences. criteria. • Design a test of a model to ascertain its reliability. Modeling tools are used to develop questions, predictions, and explanations; analyze and identify flaws in systems; and communicate ideas. Models are used to build and revise scientific explanations and proposed engineered systems. Measurements and observations are used to revise models and designs. 68 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Developing and Using • Develop and/or use a model • Collaboratively develop and/ • Develop or modify a model— • Develop, revise, and/or use a Models to represent amounts, or revise a model based on based on evidence—to match model based on evidence to relationships, relative scales evidence that shows the what happens if a variable illustrate and/or predict the (bigger, smaller), and/or relationships among variables or component of a system is relationships between systems patterns in the natural and for frequent and regular changed. or between components of a designed world(s). occurring events. • Use and/or develop a model of system. • Develop a model using an simple systems with uncertain • Develop and/or use multiple analogy, example, or abstract and less predictable factors. types of models to provide representation to describe a • Develop and/or revise a model mechanistic accounts and/or scientific principle or design to show the relationships predict phenomena, and move solution. among variables, including flexibly between model types • Develop and/or use models those that are not observable based on merits and limitations. to describe and/or predict but predict observable phenomena. phenomena. • Develop and/or use a model to predict and/or describe phenomena. • Develop a model to describe unobservable mechanisms. • Develop a simple model based • Develop a diagram or simple • Develop and/or use a model • Develop a complex model that on evidence to represent a physical prototype to convey to generate data to test ideas allows for manipulation and proposed object or tool. a proposed object, tool, or about phenomena in natural testing of a proposed process or process. or designed systems, including system. • Use a model to test cause those representing inputs • Develop and/or use a model and effect relationships or and outputs, and those at (including mathematical and interactions concerning the unobservable scales. computational) to generate data functioning of a natural or to support explanations, predict designed system. phenomena, analyze systems, and/or solve problems. Science and Engineering Practices in the Next Generation Science Standards 69

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Planning and Carrying Out Planning and carrying out Planning and carrying out Planning and carrying out Planning and carrying out Investigations investigations to answer investigations to answer investigations in 6–8 builds on investigations in 9–12 builds on questions or test solutions to questions or test solutions to K–5 experiences and progresses K–8 experiences and progresses to problems in K–2 builds on prior problems in 3–5 builds on K–2 to include investigations that use include investigations that provide Scientists and engineers plan experiences and progresses to experiences and progresses to multiple variables and provide evidence for and test conceptual, simple investigations, based on include investigations that control evidence to support explanations mathematical, physical, and and carry out investigations fair tests, which provide data to variables and provide evidence to or solutions. empirical models. in the field or laboratory, support explanations or design support explanations or design working collaboratively as solutions. solutions. well as individually. Their investigations are systematic • With guidance, plan and • Plan and conduct an Plan an investigation individually • Plan an investigation or test and require clarifying conduct an investigation in investigation collaboratively to and collaboratively, and in the a design individually and collaboration with peers (for K). produce data to serve as the design identify independent and collaboratively to produce data what counts as data and • Plan and conduct an basis for evidence, using fair dependent variables and controls, to serve as the basis for evidence identifying variables or investigation collaboratively to tests in which variables are what tools are needed to do the as part of building and revising parameters. produce data to serve as the controlled and the number of gathering, how measurements models, supporting explanations basis for evidence to answer a trials is considered. will be recorded, and how many for phenomena, or testing question. data are needed to support a solutions to problems. Consider Engineering investigations claim. possible confounding variables identify the effectiveness, or effects and evaluate the Conduct an investigation and/ investigation’s design to ensure efficiency, and durability or evaluate and/or revise the variables are controlled. of designs under different experimental design to produce • Plan and conduct an conditions. data to serve as the basis for investigation individually and evidence that meet the goals of collaboratively to produce the investigation. 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. • Plan and conduct an investigation or test a design solution in a safe and ethical manner, including considerations of environmental, social, and personal impacts. • Evaluate different ways of • Evaluate appropriate methods • Evaluate the accuracy of • Select appropriate tools to observing and/or measuring and/or tools for collecting data. various methods for collecting collect, record, analyze, and a phenomenon to determine data. evaluate data. which way can answer a question. 70 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Planning and Carrying Out • Make observations (firsthand • Make observations and/or • Collect data to produce data to • Make directional hypotheses Investigations or from media) and/or measurements to produce serve as the basis for evidence that specify what happens to measurements to collect data data to serve as the basis for to answer scientific questions a dependent variable when that can be used to make evidence for an explanation or test design solutions under a an independent variable is comparisons. of a phenomenon or to test a range of conditions. manipulated. • Make observations (firsthand design solution. • Collect data about the • Manipulate variables and collect or from media) and/or • Make predictions about what performance of a proposed data about a complex model of measurements of a proposed would happen if a variable object, tool, process, or system a proposed process or system to object, tool, or solution to changes. under a range of conditions. identify failure points or improve determine if it solves a problem • Test two different models of performance relative to criteria or meets a goal. the same proposed object, for success or other variables. • Make predictions based on tool, or process to determine prior experiences. which better meets criteria for success. Analyzing and Analyzing data in K–2 builds on Analyzing data in 3–5 builds on Analyzing data in 6–8 builds on Analyzing data in 9–12 builds on Interpreting Data prior experiences and progresses K–2 experiences and progresses K–5 experiences and progresses K–8 experiences and progresses to to collecting, recording, and to introducing quantitative to extending quantitative analysis introducing more detailed statistical sharing observations. approaches to collecting data to investigations, distinguishing analysis, the comparison of data Scientific investigations and conducting multiple trials of between correlation and sets for consistency, and the use qualitative observations. causation, and basic statistical of models to generate and analyze produce data that must When possible and feasible, techniques of data and error data. be analyzed in order to digital tools should be used. analysis. derive meaning. Because data patterns and trends are not always obvious, scientists use a range of tools—including tabulation, graphical interpretation, visualization, and statistical analysis—to identify the significant features and patterns in the data. Scientists identify sources of error in the investigations and calculate the degree of certainty in the results. Modern technology makes the collection of large data sets much easier, providing secondary sources for analysis. Science and Engineering Practices in the Next Generation Science Standards 71

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Analyzing and • Record information • Represent data in tables and/or • Construct, analyze, and/or • Analyze data using tools, Interpreting Data (observations, thoughts, and various graphical displays (bar interpret graphical displays of technologies, and/or models (e.g., ideas). graphs, pictographs, and/or pie data and/or large data sets to computational, mathematical) in (continued) • Use and share pictures, charts) to reveal patterns that identify linear and nonlinear order to make valid and reliable drawings, and/or writings of indicate relationships. relationships. scientific claims or determine an observations. • Use graphical displays (e.g., optimal design solution. Engineering investigations • Use observations (firsthand maps, charts, graphs, and/or include analysis of data or from media) to describe tables) of large data sets to collected in the tests patterns and/or relationships identify temporal and spatial of designs. This allows in the natural and designed relationships. comparison of different world(s) in order to answer • Distinguish between causal scientific questions and solve and correlational relationships solutions and determines problems. in data. how well each meets specific • Compare predictions (based • Analyze and interpret data design criteria—that is, on prior experiences) to what to provide evidence for which design best solves occurred (observable events). phenomena. the problem within given • Analyze and interpret data to • Apply concepts of statistics and • Apply concepts of statistics constraints. Like scientists, make sense of phenomena, probability (including mean, and probability (including engineers require a range using logical reasoning, median, mode, and variability) determining function fits to of tools to identify patterns mathematics, and/or to analyze and characterize data, slope, intercept, and within data and interpret the computation. data, using digital tools when correlation coefficient for linear results. Advances in science feasible. fits) to scientific and engineering questions and problems, using make analysis of proposed digital tools when feasible. solutions more efficient and effective. • Consider limitations of data • Consider limitations of data analysis (e.g., measurement analysis (e.g., measurement error) and/or seek to improve error, sample selection) when precision and accuracy of data analyzing and interpreting data. with better technological tools and methods (e.g., multiple trials). • Compare and contrast data • Analyze and interpret data • Compare and contrast various collected by different groups in to determine similarities and types of data sets (e.g., self- order to discuss similarities and differences in findings. generated, archival) to examine differences in their findings. consistency of measurements and observations. 72 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Analyzing and • Analyze data from tests of an • Analyze data to refine a • Analyze data to define an • Evaluate the impact of new data Interpreting Data object or tool to determine if it problem statement or the optimal operational range for a on a working explanation and/ works as intended. design of a proposed object, proposed object, tool, process, or model of a proposed process tool, or process. or system that best meets or system. • Use data to evaluate and refine criteria for success. • Analyze data to identify design design solutions. features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success. Using Mathematics and Mathematical and computational Mathematical and computational Mathematical and computational Mathematical and computational Computational Thinking thinking in K–2 builds on prior thinking in 3–5 builds on K–2 thinking in 6–8 builds on K–5 thinking in 9–12 builds on K–8 experience and progresses to experiences and progresses experiences and progresses to and experiences and progresses recognizing that mathematics can to extending quantitative identifying patterns in large data to using algebraic thinking and In both science and be used to describe the natural measurements to a variety of sets and using mathematical analysis, a range of linear and and designed world(s). physical properties and using concepts to support explanations non-linear functions, including engineering, mathematics computation and mathematics and arguments. trigonometric functions, and computation are to analyze data and compare exponentials and logarithms, and fundamental tools for alternative design solutions. computational tools for statistical representing physical analysis to analyze, represent, and variables and their model data. Simple computational simulations are created and used relationships. They are used based on mathematical models of for a range of tasks such as basic assumptions. constructing simulations; solving equations exactly • Decide when to use qualitative • Decide if qualitative or or approximately; and vs. quantitative data. quantitative data are best to recognizing, expressing, determine whether a proposed object or tool meets criteria for and applying quantitative success. relationships. • Use counting and numbers to • Organize simple data sets to • Use digital tools (e.g., • Create and/or revise a identify and describe patterns reveal patterns that suggest computers) to analyze very computational model or Mathematical and in the natural and designed relationships. large data sets for patterns and simulation of a phenomenon, computational approaches world(s). trends. designed device, process, or enable scientists and system. engineers to predict the • Describe, measure, and/or • Describe, measure, estimate, • Use mathematical • Use mathematical, behavior of systems and compare quantitative attributes and/or graph quantities such representations to describe computational, and/or test the validity of such of different objects and display as area, volume, weight, and and/or support scientific algorithmic representations of predictions. the data using simple graphs. time to address scientific and conclusions and design phenomena or design solutions engineering questions and solutions. to describe and/or support claims problems. and/or explanations. Science and Engineering Practices in the Next Generation Science Standards 73

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Using Mathematics and • Use quantitative data to • Create and/or use graphs • Create algorithms (a series • Apply techniques of algebra Computational Thinking compare two alternative and/or charts generated from of ordered steps) to solve a and functions to represent and solutions to a problem. simple algorithms to compare problem. solve scientific and engineering (continued) alternative solutions to an • Apply mathematical concepts problems. engineering problem. and/or processes (such as • Use simple limit cases to test ratio, rate, percent, basic mathematical expressions, operations, and simple algebra) computer programs, algorithms, to scientific and engineering or simulations of a process questions and problems. or system to see if a model • Use digital tools and/or “makes sense” by comparing the mathematical concepts and outcomes with what is known arguments to test and compare about the real world. proposed solutions to an • Apply ratios, rates, percentages, engineering design problem. and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units (such as mg/mL, kg/m3, acre-feet, etc.). Constructing Explanations Constructing explanations and Constructing explanations and Constructing explanations and Constructing explanations and and Designing Solutions designing solutions in K–2 designing solutions in 3–5 designing solutions in 6–8 designing solutions in 9–12 builds builds on prior experiences and builds on K–2 experiences and builds on K–5 experiences and on K–8 experiences and progresses progresses to the use of evidence progresses to the use of evidence progresses to include constructing to explanations and designs that The end products of science and ideas in constructing in constructing explanations that explanations and designing are supported by multiple and evidence-based accounts of specify variables that describe solutions supported by multiple independent student-generated are explanations, and the natural phenomena and designing and predict phenomena and in sources of evidence consistent sources of evidence consistent end products of engineering solutions. designing multiple solutions to with scientific ideas, principles, with scientific ideas, principles, and are solutions. design problems. and theories. theories. The goal of science is the construction of theories that provide explanatory accounts of the world. A theory becomes accepted when it has multiple lines of empirical evidence and greater explanatory power of phenomena than previous theories. 74 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Constructing Explanations • Use information from • Construct an explanation of • Construct an explanation • Make a quantitative and/or and Designing Solutions observations (firsthand and observed relationships (e.g., that includes qualitative or qualitative claim regarding the from media) to construct an the distribution of plants in a quantitative relationships relationship between dependent evidence-based account for backyard). between variables that and independent variables. natural phenomena. predict(s) and/or describe(s) phenomena. The goal of engineering • Construct an explanation using design is to find a systematic models or representations. solution to problems that is based on scientific • Use evidence (e.g., • Construct a scientific • Construct and revise an knowledge and models of measurements, observations, explanation based on valid and explanation based on valid and patterns) to construct or reliable evidence obtained from reliable evidence obtained from the material world. Each support an explanation or sources (including students’ a variety of sources (including proposed solution results design a solution to a problem. own experiments) and the students’ own investigations, from a process of balancing assumption that theories models, theories, simulations, competing criteria of and laws that describe the peer review) and the assumption desired functions, technical natural world operate today that theories and laws that as they did in the past and will describe the natural world feasibility, cost, safety, continue to do so in the future. operate today as they did in the aesthetics, and compliance • Apply scientific ideas, past and will continue to do so in with legal requirements. principles, and/or evidence to the future. The optimal choice depends construct, revise, and/or use • Apply scientific ideas, principles, on how well the proposed an explanation for real-world and/or evidence to provide an phenomena, examples, or explanation of phenomena solutions meet criteria and events. and solve design problems, constraints. taking into account possible unanticipated effects. • Identify evidence that supports • Apply scientific reasoning to • Apply scientific reasoning, theory, particular points in an show why the data or evidence and/or models to link evidence explanation. is adequate for the explanation to claims to assess the extent or conclusion. to which the reasoning and data support the explanation or conclusion. • Use tools and/or materials to • Apply scientific ideas to solve • Apply scientific ideas or • Design, evaluate, and/or refine design and/or build a device design problems. principles to design, construct, a solution to a complex real- that solves a specific problem • Generate and compare and/or test a design of an world problem, based on or a solution to a specific multiple solutions to a problem object, tool, process, or system. scientific knowledge, student- problem. based on how well they meet • Undertake a design project, generated sources of evidence, • Generate and/or compare the criteria and constraints of engaging in the design cycle, prioritized criteria, and tradeoff multiple solutions to a the design solution. to construct and/or implement considerations. problem. a solution that meets specific design criteria and constraints. • Optimize performance of a design by prioritizing criteria, making tradeoffs, testing, revising, and re-testing. Science and Engineering Practices in the Next Generation Science Standards 75

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Engaging in Argument Engaging in argument from Engaging in argument from Engaging in argument from Engaging in argument from from Evidence evidence in K–2 builds on prior evidence in 3–5 builds on K–2 evidence in 6–8 builds on K–5 evidence in 9–12 builds on K–8 experiences and progresses experiences and progresses experiences and progresses experiences and progresses to to comparing ideas and to critiquing the scientific to constructing a convincing using appropriate and sufficient Argumentation is the representations about the natural explanations or solutions argument that supports or refutes evidence and scientific reasoning and designed world(s). proposed by peers by citing claims for either explanations or to defend and critique claims and process by which evidence- relevant evidence about the solutions about the natural and explanations about the natural and based conclusions and natural and designed world(s). designed world(s). designed world(s). Arguments may solutions are reached. also come from current scientific or historical episodes in science. In science and engineering, • Identify arguments that are • Compare and refine arguments • Compare and critique two • Compare and evaluate reasoning and argument supported by evidence. based on an evaluation of the arguments on the same topic competing arguments or design based on evidence are • Distinguish between evidence presented. and analyze whether they solutions in light of currently explanations that account • Distinguish among facts, emphasize similar or different accepted explanations, new essential to identifying for all gathered evidence and reasoned judgment based evidence and/or interpretations evidence, limitations (e.g., trade- the best explanation for a those that do not. on research findings, and of facts. offs), constraints, and ethical natural phenomenon or the • Analyze why some evidence is speculation in an explanation. issues. best solution to a design relevant to a scientific question • Evaluate the claims, evidence, problem. and some is not. and/or reasoning behind • Distinguish between opinions currently accepted explanations and evidence in one’s own or solutions to determine the Scientists and engineers explanations. merits of arguments. use argumentation to listen to, compare, and evaluate • Listen actively to arguments • Respectfully provide and • Respectfully provide and • Respectfully provide and/or competing ideas and to indicate agreement or receive critiques from peers receive critiques about one’s receive critiques on scientific disagreement based on about a proposed procedure, explanations, procedures, arguments by probing reasoning methods based on merits. evidence and/or to retell the explanation, or model by citing models, and questions by and evidence and challenging main points of the argument. relevant evidence and posing citing relevant evidence and ideas and conclusions, specific questions. posing and responding to responding thoughtfully to Scientists and engineers questions that elicit pertinent diverse perspectives, and engage in argumentation elaboration and detail. determining what additional when investigating a information is required to phenomenon, testing resolve contradictions. a design solution, • Construct an argument with • Construct and/or support an • Construct, use, and/or present • Construct, use, and/or present resolving questions about evidence to support a claim. argument with evidence, data, an oral and written argument an oral and written argument measurements, building data and/or a model. supported by empirical or counter-arguments based on models, and using evidence • Use data to evaluate claims evidence and scientific data and evidence. to evaluate claims. about cause and effect. reasoning to support or refute an explanation or a model for a phenomenon or a solution to a problem. 76 NEXT GENERATION SCIENCE STANDARDS

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Engaging in Argument • Make a claim about the • Make a claim about the merit • Make an oral or written • Make and defend a claim based from Evidence effectiveness of an object, tool, of a solution to a problem by argument that supports on evidence about the natural or solution that is supported by citing relevant evidence about or refutes the advertised world or the effectiveness of relevant evidence. how it meets the criteria and performance of a device, a design solution that reflects constraints of the problem. process, or system, based on scientific knowledge and empirical evidence concerning student-generated evidence. whether or not the technology • Evaluate competing design meets relevant criteria and solutions to a real-world constraints. problem based on scientific • Evaluate competing design ideas and principles, empirical solutions based on jointly evidence, and/or logical developed and agreed-upon arguments regarding relevant design criteria. factors (e.g., economic, societal, environmental, ethical considerations). Obtaining, Evaluating, Obtaining, evaluating, and Obtaining, evaluating, and Obtaining, evaluating, and Obtaining, evaluating, and and Communicating communicating information in communicating information in communicating information in communicating information in K–2 builds on prior experiences 3–5 builds on K–2 experiences 6–8 builds on K–5 experiences 9–12 builds on K–8 experiences Information and uses observations and texts and progresses to evaluating the and progresses to evaluating the and progresses to evaluating the to communicate new information. merit and accuracy of ideas and merit and validity of ideas and validity and reliability of claims, methods. methods. methods, and designs. Scientists and engineers must be able to • Read grade-appropriate texts • Read and comprehend grade- • Critically read scientific texts • Critically read scientific literature communicate clearly and/or use media to obtain appropriate complex texts adapted for classroom use to adapted for classroom use to and persuasively the scientific and/or technical and/or other reliable media determine the central ideas determine the central ideas or ideas and methods they information to determine to summarize and obtain and/or obtain scientific and/ conclusions and/or to obtain generate. Critiquing and patterns in and/or evidence scientific and technical or technical information to scientific and/or technical about the natural and ideas and describe how they describe patterns in and/or information to summarize communicating ideas designed world(s). are supported by evidence.  evidence about the natural complex evidence, concepts, individually and in groups • Compare and/or combine and designed world(s). processes, or information is a critical professional across complex texts and/or presented in a text by activity. other reliable media to support paraphrasing them in simpler the engagement in other but still accurate terms. scientific and/or engineering practices. • Describe how specific images • Combine information in • Integrate qualitative and/or • Compare, integrate, and (e.g., a diagram showing how written text with that quantitative scientific and/ evaluate sources of information a machine works) support a contained in corresponding or technical information presented in different media scientific or engineering idea. tables, diagrams, and/or charts in written text with that or formats (e. g., visually, to support the engagement contained in media and visual quantitatively) and in words in other scientific and/or displays to clarify claims and in order to address a scientific engineering practices. findings. question or solve a problem. Science and Engineering Practices in the Next Generation Science Standards 77

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Alternate Arrangement of the Practices Matrix Science and Engineering K–2 Condensed Practices 3–5 Condensed Practices 6–8 Condensed Practices 9–12 Condensed Practices Practices Obtaining, Evaluating, • Obtain information using • Obtain and combine • Gather, read, and synthesize • Gather, read, and evaluate and Communicating various texts, text features information from books and/or information from multiple scientific and/or technical (e.g., headings, tables of other reliable media to explain appropriate sources and information from multiple Information contents, glossaries, electronic phenomena or solutions to a assess the credibility, accuracy, authoritative sources, assessing (continued) menus, icons), and other design problem. and possible bias of each the evidence and usefulness of media that will be useful in publication and the methods each source. answering a scientific question used, and describe how they • Evaluate the validity and Communicating information and/or supporting a scientific are supported or not supported reliability of and/or synthesize and ideas can be done claim. by evidence. multiple claims, methods, and/or in multiple ways: using • Evaluate data, hypotheses, designs that appear in scientific and/or conclusions in scientific and technical texts or media tables, diagrams, graphs, and technical texts in light reports, verifying the data when models, and equations as of competing information or possible. well as orally, in writing, accounts. and through extended discussions. Scientists • Communicate information or • Communicate scientific and/ • Communicate scientific and/ • Communicate scientific and/or and engineers employ design ideas and/or solutions or technical information orally or technical information (e.g., technical information or ideas with others in oral and/or and/or in written formats, about a proposed object, (e.g., about phenomena and/or multiple sources to obtain written forms using models, including various forms of tool, process, system) in the process of development and information that is used drawings, writing, or numbers media as well as tables, writing and/or through oral the design and performance of to evaluate the merit and that provide detail about diagrams, and charts. presentations. a proposed process or system) validity of claims, methods, scientific ideas, practices, and/ in multiple formats (including and designs. or design ideas. orally, graphically, textually, and mathematically). 78 NEXT GENERATION SCIENCE STANDARDS