Science

SEPs1: Asking Questions and Defining Problems
Asking questions and defining problems in K-12 builds on prior experiences and progresses to simple descriptive questions.

SEPs2: Developing and Using Models
Modeling in K-12 builds on prior experiences and progresses to include using and developing models (i.e., diagrams, drawing, physical replica, diorama, dramatization, or storyboard) that represent concrete events or design solutions.

SEPs3: Planning and Carrying Out Investigations
Planning and carrying out K-12 investigations to answer questions or test solutions to problems build on prior experiences and progresses to simple investigations, based on fair tests, which provide data to support explanations or design solutions.

SEPs4: Analyzing and Interpreting Data
Analyzing data in K-12 builds on prior experiences and progresses to collecting, recording, and sharing observations.

SEPs5: Using Mathematics and Computational Thinking
Using mathematics and computational thinking in K-12 builds logical reasoning and problem-solving skills.

SEPs6: Constructing Explanations and Designing Solutions
Constructing explanations and designing solutions in K-12 builds on prior experiences and progresses to the use of evidence and ideas in constructing evidence-based accounts of natural phenomena and designing solutions.

SEPs7: Engaging in Argument from Evidence
Engaging in argument from evidence in K-12 builds on prior experiences and progresses to comparing ideas and representations about the natural and designed world(s).

SEPs8: Obtaining, Evaluating, and Communicating Information
Obtaining, evaluating, and communicating information in K-12 builds on prior experiences and uses observations and texts to communicate new information.

CCCs1: Patterns
Structures or events are often consistent and repeated.

CCCs2: Cause and Effect
Events gave causes, sometimes esimple, sometimes multifaceted.

CCCs3: Scale, Proportion, and Quantity
Different measures of size and time affect a system's structure, performance, and our ability to observe phenomena.

CCCs4: Systems and System Models
A set of connected things or parts forming a complete whole.

CCCs5: Energy and Matter
Tracking energy and matter flows, into, out of, and within systems helps one understand their systems behaviors.

CCCs6: Structure and Function
The ways an object is shaped or structured determines many of its properties and functions.

CCCs7: Stability and Change
Over time, a system might stay the same or become different, depending on a variety of factors.

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Observed patterns in nature guide organization and classification and prompt questions about relationships and causes underlying them.

Primary (K-2)
• Patterns in the natural and human designed world can be observed, used to describe phenomena, and used as evidence.
Elementary (3-5)
• Similarities and differences in patterns can be used to sort, classify, communicate and analyze simple rates of change for natural phenomena and designed products.
• Patterns of change can be used to make predictions
• Patterns can be used as evidence to support an explanation.
Middle (6-8)
• Macroscopic patterns are related to the nature of microscopic and atomic-level structure.
• Graphs, charts, and images can be used to identify patterns in data.
• Patterns in rates of change and other numerical relationships can provide information about natural systems.
• Patterns can be used to identify cause-and-effect relationships.
High (9-12)
• 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.
• Empirical evidence is needed to identify patterns.
• Classifications or explanations used at one scale may fail or need revision when information from smaller or larger scales is introduced; thus requiring improved investigations and experiments.
• Patterns of performance of designed systems can be analyzed and interpreted to reengineer and improve the system.
• Mathematical representations are needed to identify some patterns.

“Patterns exist everywhere—in regularly occurring shapes or structures and in repeating events and relationships. For example, patterns are discernible in the symmetry of flowers and snowflakes, the cycling of the seasons, and the repeated base pairs of DNA.”

While there are many patterns in nature, they are not the norm since there is a tendency for disorder to increase (e.g. it is far more likely for a broken glass to scatter than for scattered bits to assemble themselves into a whole glass). In some cases, order seems to emerge from chaos, as when a plant sprouts, or a tornado appears amidst scattered storm clouds. It is in such examples that patterns exist and the beauty of nature is found. “Noticing patterns is often a first step to organizing phenomena and asking scientific questions about why and how the patterns occur.”

“Once patterns and variations have been noted, they lead to questions; scientists seek explanations for observed patterns and for the similarity and diversity within them. Engineers often look for and analyze patterns, too. For example, they may diagnose patterns of failure of a designed system under test in order to improve the design, or they may analyze patterns of daily and seasonal use of power to design a system that can meet the fluctuating needs.”

Patterns figure prominently in the science and engineering practice of “Analyzing and Interpreting Data.” Recognizing patterns is a large part of working with data. Students might look at geographical patterns on a map, plot data values on a chart or graph, or visually inspect the appearance of an organism or mineral. The crosscutting concept of patterns is also strongly associated with the practice of “Using Mathematics and Computational Thinking.” It is often the case that patterns are identified best using mathematical concepts. As Richard Feynman said, “To those who do not know mathematics it is difficult to get across a real feeling as to the beauty, the deepest beauty, of nature. If you want to learn about nature, to appreciate nature, it is necessary to understand the language that she speaks in.”

The human brain is remarkably adept at identifying patterns, and students progressively build upon this innate ability throughout their school experiences. The following table lists the guidelines used by the writing team for how this progression plays out across K-12, with examples of performance expectations drawn from the Science standards.

Events have causes, sometimes simple, sometimes multifaceted. Deciphering causal relationships, and the mechanisms by which they are mediated, is a major activity of science and engineering.

Primary (K-2)
• Simple tests can be designed to gather evidence to support or refute student ideas about causes.
• Events have causes that generate observable patterns.
Elementary (3-5)
• Cause and effect relationships are routinely identified, tested, and used to explain change.
• Events that occur together with regularity might or might not be a cause and effect relationship.
Middle (6-8)
• Cause and effect relationships may be used to predict phenomena in natural or designed systems.
• Phenomena may have more than one cause, and some cause and effect relationships in systems can only be described using probability.
• Relationships can be classified as causal or correlational, and correlation does not necessarily imply causation.
High (9-12)
• Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.
• Systems can be designed to cause a desired effect.
• Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system.
• Changes in systems may have various causes that may not have equal effects.

Cause and effect is often the next step in science, after a discovery of patterns or events that occur together with regularity. A search for the underlying cause of a phenomenon has sparked some of the most compelling and productive scientific investigations. “Any tentative answer, or ‘hypothesis,’ that A causes B requires a model or mechanism for the chain of interactions that connect A and B. For example, the notion that diseases can be transmitted by a person’s touch was initially treated with skepticism by the medical profession for lack of a plausible mechanism. Today infectious diseases are well understood as being transmitted by the passing of microscopic organisms (bacteria or viruses) between an infected person and another. A major activity of science is to uncover such causal connections, often with the hope that understanding the mechanisms will enable predictions and, in the case of infectious diseases, the design of preventive measures, treatments, and cures.”.

“In engineering, the goal is to design a system to cause a desired effect, so cause-and-effect relationships are as much a part of engineering as of science. Indeed, the process of design is a good place to help students begin to think in terms of cause and effect, because they must understand the underlying causal relationships in order to devise and explain a design that can achieve a specified objective.”.

When students perform the practice of “Planning and Carrying Out Investigations,” they often address cause and effect. At early ages, this involves “doing” something to the system of study and then watching to see what happens. At later ages, experiments are set up to test the sensitivity of the parameters involved, and this is accomplished by making a change (cause) to a single component of a system and examining, and often quantifying, the result (effect). Cause and effect is also closely associated with the practice of “Engaging in Argument from Evidence.” In scientific practice, deducing the cause of an effect is often difficult, so multiple hypotheses may coexist. For example, though the occurrence (effect) of historical mass extinctions of organisms, such as the dinosaurs, is well established, the reason or reasons for the extinctions (cause) are still debated, and scientists develop and debate their arguments based on different forms of evidence. When students engage in scientific argumentation, it is often centered about identifying the causes of an effect.

In considering phenomena, it is critical to recognize what is relevant at different size, time, and energy scales, and to recognize proportional relationships between different quantities as scales change.

Primary (K-2)
• Relative scales allow objects and events to be compared and described (e.g., bigger and smaller; hotter and colder; faster and slower).
• Standard units are used to measure length.
Elementary (3-5)
• Natural objects and/or observable phenomena exist from the very small to the immensely large or from very short to very long time periods.
• Standard units are used to measure and describe physical quantities such as weight, time, temperature, and volume.
Middle (6-8)
• Time, space, and energy phenomena can be observed at various scales using models to study systems that are too large or too small.
• Proportional relationships (e.g. speed as the ratio of distance traveled to time taken) among different types of quantities provide information about the magnitude of properties and processes.
• Phenomena that can be observed at one scale may not be observable at another scale.
• The observed function of natural and designed systems may change with scale.
• Scientific relationships can be represented through the use of algebraic expressions and equations.
High (9-12)
• The significance of a phenomenon is dependent on the scale, proportion, and quantity at which it occurs.
• Algebraic thinking is used to examine scientific data and predict the effect of a change in one variable on another (e.g., linear growth vs. exponential growth).
• Using the concept of orders of magnitude allows one to understand how a model at one scale relates to a model at another scale.
• Some systems can only be studied indirectly as they are too small, too large, too fast, or too slow to observe directly.
• Patterns observable at one scale may not be observable or exist at other scales.

Scale, Proportion and Quantity are important in both science and engineering. These are fundamental assessments of dimension that form the foundation of observations about nature. Before an analysis of function or process can be made (the how or why), it is necessary to identify the what. These concepts are the starting point for scientific understanding, whether it is of a total system or its individual components. Any student who has ever played the game “twenty questions” understands this inherently, asking questions such as, “Is it bigger than a bread box?” in order to first determine the object’s size.

An understanding of scale involves not only understanding systems and processes vary in size, time span, and energy, but also different mechanisms operate at different scales. In engineering, “no structure could be conceived, much less constructed, without the engineer’s precise sense of scale... At a basic level, in order to identify something as bigger or smaller than something else—and how much bigger or smaller—a student must appreciate the units used to measure it and develop a feel for quantity.” (p. 90) “The ideas of ratio and proportionality as used in science can extend and challenge students’ mathematical understanding of these concepts. To appreciate the relative magnitude of some properties or processes, it may be necessary to grasp the relationships among different types of quantities—for example, speed as the ratio of distance traveled to time taken, density as a ratio of mass to volume. This use of ratio is quite different than a ratio of numbers describing fractions of a pie. Recognition of such relationships among different quantities is a key step in forming mathematical models that interpret scientific data.”

The crosscutting concept of Scale, Proportion, and Quantity figures prominently in the practices of “Using Mathematics and Computational Thinking” and in “Analyzing and Interpreting Data.” This concept addresses taking measurements of structures and phenomena, and these fundamental observations are usually obtained, analyzed, and interpreted quantitatively. This crosscutting concept also figures prominently in the practice of “Developing and Using Models.” Scale and proportion are often best understood using models. For example, the relative scales of objects in the solar system or of the components of an atom are difficult to comprehend mathematically (because the numbers involved are either so large or so small), but visual or conceptual models make them much more understandable (e.g., if the solar system were the size of a penny, the Milky Way galaxy would be the size of Texas).

A system is an organized group of related objects or components; models can be used for understanding and predicting the behavior of systems.

Primary (K-2)
• Systems in the natural and designed world have parts that work together.
• Objects and organisms can be described in terms of their parts
Elementary (3-5)
• A system can be described in terms of its components and their interactions.
• A system is a group of related parts that make up a whole and can carry out functions its individual parts cannot.
Middle (6-8)
• Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy and matter flows within systems.
• Systems may interact with other systems; they may have sub-systems and be a part of larger complex systems.
• Models are limited in that they only represent certain aspects of the system under study.
High (9-12)
• 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 (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.
• 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 can be designed to do specific tasks.

Systems and System Models are useful in science and engineering because the world is complex, so it is helpful to isolate a single system and construct a simplified model of it. “To do this, scientists and engineers imagine an artificial boundary between the system in question and everything else. They then examine the system in detail while treating the effects of things outside the boundary as either forces acting on the system or flows of matter and energy across it—for example, the gravitational force due to Earth on a book lying on a table or the carbon dioxide expelled by an organism. Consideration of flows into and out of the system is a crucial element of system design. In the laboratory or even in field research, the extent to which a system under study can be physically isolated or external conditions controlled is an important element of the design of an investigation and interpretation of results…The properties and behavior of the whole system can be very different from those of any of its parts, and large systems may have emergent properties, such as the shape of a tree, that cannot be predicted in detail from knowledge about the components and their interactions.”

“Models can be valuable in predicting a system’s behaviors or in diagnosing problems or failures in its functioning, regardless of what type of system is being examined… In a simple mechanical system, interactions among the parts are describable in terms of forces among them that cause changes in motion or physical stresses. In more complex systems, it is not always possible or useful to consider interactions at this detailed mechanical level, yet it is equally important to ask what interactions are occurring (e.g., predator-prey relationships in an ecosystem) and to recognize that they all involve transfers of energy, matter, and (in some cases) information among parts of the system… Any model of a system incorporates assumptions and approximations; the key is to be aware of what they are and how they affect the model’s reliability and precision. Predictions may be reliable but not precise or, worse, precise but not reliable; the degree of reliability and precision needed depends on the use to which the model will be put.”

Tracking energy and matter flows, into, out of, and within systems helps one understand their system’s behavior.

Primary (K-2)
• Objects may break into smaller pieces and be put together into larger pieces, or change shapes.
Elementary (3-5)
• Energy can be transferred in various ways and between objects.
• Matter is made of particles.
• Matter flows and cycles can be tracked in terms of the weight of the substances before and after a process occurs. The total weight of the substances does not change. This is what is meant by conservation of matter. Matter is transported into, out of, and within systems.
Middle (6-8)
• Matter is conserved because atoms are conserved in physical and chemical processes.
• Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).
• Within a natural system, the transfer of energy drives the motion and/or cycling of matter.
• The transfer of energy can be tracked as energy flows through a natural system.
High (9-12)
• In nuclear processes, atoms are not conserved, but the total number of protons plus neutrons is conserved.
• The total amount of energy and matter in closed systems is conserved.
• Changes of energy and matter in a system can be described in terms of energy and matter flows into, out of, and within that system.
• Energy cannot be created or destroyed—it only moves between one place and another place, between objects and/or fields, or between systems. Energy drives the cycling of matter within and between systems.

Energy and Matter are essential concepts in all disciplines of science and engineering, often in connection with systems. “The supply of energy and of each needed chemical element restricts a system’s operation—for example, without inputs of energy (sunlight) and matter (carbon dioxide and water), a plant cannot grow. Hence, it is very informative to track the transfers of matter and energy within, into, or out of any system under study.

“In many systems there also are cycles of various types. In some cases, the most readily observable cycling may be of matter—for example, water going back and forth between Earth’s atmosphere and its surface and subsurface reservoirs. Any such cycle of matter also involves associated energy transfers at each stage, so to fully understand the water cycle, one must model not only how water moves between parts of the system but also the energy transfer mechanisms that are critical for that motion.

“Consideration of energy and matter inputs, outputs, and flows or transfers within a system or process are equally important for engineering. A major goal in design is to maximize certain types of energy output while minimizing others, in order to minimize the energy inputs needed to achieve a desired task.”

The way an object is shaped or structured determines many of its properties and functions.

Primary (K-2)
• The shape and stability of structures of natural and designed objects are related to their function(s).
Elementary (3-5)
• Different materials have different substructures, which can sometimes be observed.
• Substructures have shapes and parts that serve functions.
Middle (6-8)
• Structures can be designed to serve particular functions by taking into account properties of different materials, and how materials can be shaped and used.
• Complex and microscopic structures and systems can be visualized, modeled, and used to describe how their function depends on the shapes, composition, and relationships among its parts, therefore complex natural structures/systems can be analyzed to determine how they function.
High (9-12)
• Investigating or designing new systems or structures requires a detailed examination of the properties of different materials, the structures of different components, and connections of components to reveal its function and/or solve a problem.
• The functions and properties of natural and designed objects and systems can be inferred from their overall structure, the way their components are shaped and used, and the molecular substructures of its various materials.

Structure and Function are complementary properties. “The shape and stability of structures of natural and designed objects are related to their function(s). The functioning of natural and built systems alike depends on the shapes and relationships of certain key parts as well as on the properties of the materials from which they are made. A sense of scale is necessary in order to know what properties and what aspects of shape or material are relevant at a particular magnitude or in investigating particular phenomena—that is, the selection of an appropriate scale depends on the question being asked. For example, the substructures of molecules are not particularly important in understanding the phenomenon of pressure, but they are relevant to understanding why the ratio between temperature and pressure at constant volume is different for different substances.

“Similarly, understanding how a bicycle works is best addressed by examining the structures and their functions at the scale of, say, the frame, wheels, and pedals. However, building a lighter bicycle may require knowledge of the properties (such as rigidity and hardness) of the materials needed for specific parts of the bicycle. In that way, the builder can seek less dense materials with appropriate properties; this pursuit may lead in turn to an examination of the atomic-scale structure of candidate materials. As a result, new parts with the desired properties, possibly made of new materials, can be designed and fabricated.”

For both designed and natural systems, conditions that affect stability and factors that control rates of change are critical elements to consider and understand.

Primary (K-2)
• Things may change slowly or rapidly.
• Some things stay the same while other things change.
Elementary (3-5)
• Change is measured in terms of differences over time and may occur at different rates.
• Some systems appear stable, but over long periods of time will eventually change.
Middle (6-8)
• Stability might be disturbed either by sudden events or gradual changes that accumulate over time.
• Explanations of stability and change in natural or designed systems can be constructed by examining the changes over time and processes at different scales, including the atomic scale.
• Small changes in one part of a system might cause large changes in another part.
• Systems in dynamic equilibrium are stable due to a balance of feedback mechanisms.
High (9-12)
• Much of science deals with constructing explanations of how things change and how they remain stable.
• Systems can be designed for greater or lesser stability.
• Feedback (negative or positive) can stabilize or destabilize a system.
• Change and rates of change can be quantified and modeled over very short or very long periods of time. Some system changes are irreversible.

Stability and Change are the primary concerns of many, if not most scientific and engineering endeavors. “Stability denotes a condition in which some aspects of a system are unchanging, at least at the scale of observation. Stability means that a small disturbance will fade away—that is, the system will stay in, or return to, the stable condition. Such stability can take different forms, with the simplest being a static equilibrium, such as a ladder leaning on a wall. By contrast, a system with steady inflows and outflows (i.e., constant conditions) is said to be in dynamic equilibrium. For example, a dam may be at a constant level with steady quantities of water coming in and out. . . . A repeating pattern of cyclic change—such as the moon orbiting Earth—can also be seen as a stable situation, even though it is clearly not static.

“An understanding of dynamic equilibrium is crucial to understanding the major issues in any complex system—for example, population dynamics in an ecosystem or the relationship between the level of atmospheric carbon dioxide and Earth’s average temperature. Dynamic equilibrium is an equally important concept for understanding the physical forces in matter. Stable matter is a system of atoms in dynamic equilibrium.

“In designing systems for stable operation, the mechanisms of external controls and internal ‘feedback’ loops are important design elements; feedback is important to understanding natural systems as well. A feedback loop is any mechanism in which a condition triggers some action that causes a change in that same condition, such as the temperature of a room triggering the thermostatic control that turns the room’s heater on or off.

“A system can be stable on a small time scale, but on a larger time scale it may be seen to be changing. For example, when looking at a living organism over the course of an hour or a day, it may maintain stability; over longer periods, the organism grows, ages, and eventually dies. For the development of larger systems, such as the variety of living species inhabiting Earth or the formation of a galaxy, the relevant time scales may be very long indeed; such processes occur over millions or even billions of years.”

A practice of science is to ask and refine questions that lead to descriptions and explanations of how the natural and designed world works and which can be empirically tested.

Primary (K-2)

Asking questions and defining problems in K–2 builds on prior experiences and progresses to simple descriptive questions.

• Ask and/or identify questions that can be answered by an investigation.
• Define a simple problem that can be solved through the development of a new or improved object or tool.

Elementary (3-5)

Asking questions and defining problems in grades 3–5 builds from grades K–2 experiences and progresses to specifying qualitative relationships.

• Ask questions about what would happen if a variable is changed.
• Identify scientific (testable) and non-scientific (non-testable) questions.
• Ask questions that can be investigated and predict reasonable outcomes based on patterns such as cause and effect relationships.
• Use prior knowledge to describe problems that can be solved.
• Define a simple design problem that can be solved through the development of an object, tool, process, or system and includes several criteria for success and constraints on materials, time, or cost.

Middle (6-8)

Asking questions and defining problems in grades 6–8 builds from grades K–5 experiences and progresses to specifying relationships between variables and clarifying arguments and models.

• Ask questions that require sufficient and appropriate empirical evidence to answer.
• Ask questions that arise from careful observation of phenomena, models, or unexpected results, to clarify and/or seek additional information.
• Ask questions to identify and/or clarify evidence and/or the premise(s) of an argument.
• Ask questions to determine relationships between independent and dependent variables and relationships in models.
• Ask questions to clarify and/or refine a model, an explanation, or an engineering problem.
• 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.
• 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.
• Ask questions that challenge the premise(s) of an argument or the interpretation of a data set.

High (9-12)

Asking questions and defining problems in 9–12 builds on grades K–8 experiences and progresses to formulating, refining, and evaluating empirically testable questions and design problems using models and simulations.

• Ask questions that arise from careful observation of phenomena, or unexpected results, to clarify and/or seek additional information.
• Ask questions that arise from examining models or a theory, to clarify and/or seek additional information and relationships.
• Ask questions to determine relationships, including quantitative relationships, between independent and dependent variables.
• Ask questions to clarify and refine a model, an explanation, or an engineering problem.
• Evaluate a question to determine if it is testable and relevant.
• 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.
• Ask and/or evaluate questions that challenge the premise(s) of an argument, the interpretation of a data set, or the suitability of the design.
• 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.
• Analyze complex real-world problems by specifying criteria and constraints for successful solutions.

Students at any grade level should be able to ask questions of each other about the texts they read, the features of the phenomena they observe, and the conclusions they draw from their models or scientific investigations. For engineering, they should ask questions to define the problem to be solved and to elicit ideas that lead to the constraints and specifications for its solution.

Scientific questions arise in a variety of ways. They can be driven by curiosity about the world, inspired by the predictions of a model, theory, or findings from previous investigations, or they can be stimulated by the need to solve a problem. Scientific questions are distinguished from other types of questions in that the answers lie in explanations supported by empirical evidence, including evidence gathered by others or through investigation.

While science begins with questions, engineering begins with defining a problem to solve. However, engineering may also involve asking questions to define a problem, such as: What is the need or desire that underlies the problem? What are the criteria for a successful solution? Other questions arise when generating ideas, or testing possible solutions, such as: What are the possible tradeoffs? What evidence is necessary to determine which solution is best?

Whether engaged in science or engineering, the ability to ask good questions and clearly define problems is essential for everyone. The progression of this practice summarizes what students should be able to do by the end of each grade band. Each of the examples of asking questions leads to students engaging in other scientific practices.

A practice of both science and engineering is to use and construct models as helpful tools for representing ideas and explanations. These tools include diagrams, drawings, physical replicas, mathematical representations, analogies, and computer simulations.

Primary (K-2)

Modeling in K–2 builds on prior experiences and progresses to include using and developing models (i.e., diagram, drawing, physical replica, diorama, dramatization, or storyboard) that represent concrete events or design solutions.

• Distinguish between a model and the actual object, process, and/or events the model represents.
• Compare models to identify common features and differences.
• Develop and/or use a model to represent amounts, relationships, relative scales (bigger, smaller), and/or patterns in the natural and designed world(s).
• Develop a simple model based on evidence to represent a proposed object or tool

Elementary (3-5)

Modeling in 3–5 builds on K–2 experiences and progresses to building and revising simple models and using models to represent events and design solutions.

• Identify limitations of models.
• Collaboratively develop and/or revise a model based on evidence that shows the relationships among variables for frequent and regular occurring events.
• Develop a model using an analogy, example, or abstract representation to describe a scientific principle or design solution.
• Develop and/or use models to describe and/or predict phenomena.
• Develop a diagram or simple physical prototype to convey a proposed object, tool, or process.
• Use a model to test cause and effect relationships or interactions concerning the functioning of a natural or designed system

Middle (6-8)

Modeling in 6–8 builds on K–5 experiences and progresses to developing, using, and revising models to describe, test, and predict more abstract phenomena and design systems.

• Evaluate limitations of a model for a proposed object or tool.
• Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed.
• Use and/or develop a model of simple systems with uncertain and less predictable factors.
• Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.
• Develop and/or use a model to predict and/or describe phenomena.
• Develop a model to describe unobservable mechanisms.
• 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.

High (9-12)

Modeling in 9–12 builds on K–8 experiences and progresses to using, synthesizing, and developing models to predict and show relationships among variables between systems and their components in the natural and designed world(s).

• 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.
• Design a test of a model to ascertain its reliability.
• 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.
• 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.
• Use a model to provide mechanistic accounts of phenomena.
• Develop a complex model that allows for manipulation and testing of a proposed process or system.
• Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

Modeling can begin in the earliest grades, with students’ models progressing from concrete “pictures” and/or physical scale models (e.g., a toy car) to more abstract representations of relevant relationships in later grades, such as a diagram representing forces on a particular object in a system.

Models include diagrams, physical replicas, mathematical representations, analogies, and computer simulations. Although models do not correspond exactly to the real world, they bring certain features into focus while obscuring others. All models contain approximations and assumptions that limit the range of validity and predictive power, so it is important for students to recognize their limitations.

In science, models are used to represent a system (or parts of a system) under study, to aid in the development of questions and explanations, to generate data that can be used to make predictions, and to communicate ideas to others. Students can be expected to evaluate and refine models through an iterative cycle of comparing their predictions with the real world and then adjusting them to gain insights into the phenomenon being modeled. As such, models are based upon evidence. When new evidence is uncovered that the models can’t explain, models are modified.

In engineering, models may be used to analyze a system to see where or under what conditions flaws might develop, or to test possible solutions to a problem. Models can also be used to visualize and refine a design, to communicate a design’s features to others, and as prototypes for testing design performance.

Scientists and engineers plan and carry out investigations in the field or laboratory, working collaboratively as well as individually. Their investigations are systematic and require clarifying what counts as data and identifying variables or parameters.

Primary (K-2)

With guidance, plan and conduct an investigation in collaboration with peers. Plan and conduct an investigation collaboratively to produce data to serve as the basis for evidence to answer a question. Evaluate different ways of observing and/or measuring a phenomenon to determine which way can answer a question. Make observations (firsthand or from media) to collect data that can be used to make comparisons. Make observations (firsthand or from media) and/or measurements of a proposed object or tool or solution to determine if it solves a problem or meets a goal. Make predictions based on prior experiences.

• With guidance, plan and conduct an investigation in collaboration with peers.
• Plan and conduct an investigation collaboratively to produce data to serve as the basis for evidence to answer a question.
• Evaluate different ways of observing and/or measuring a phenomenon to determine which way can answer a question.
• Make observations (firsthand or from media) to collect data that can be used to make comparisons.
• Make observations (firsthand or from media) and/or measurements of a proposed object or tool or solution to determine if it solves a problem or meets a goal.
• Make predictions based on prior experiences.

Elementary (3-5)

Planning and carrying out investigations to answer questions or test solutions to problems in 3–5 builds on K–2 experiences and progresses to include investigations that control variables and provide evidence to support explanations or design solutions.

• Plan and conduct an investigation collaboratively to produce data to serve as the basis for evidence, using fair tests in which variables are controlled and the number of trials considered.
• Evaluate appropriate methods and/or tools for collecting data.
• Make observations and/or measurements to produce data to serve as the basis for evidence for an explanation of a phenomenon or test a design solution.
• Make predictions about what would happen if a variable changes.
• Test two different models of the same proposed object, tool, or process to determine which better meets criteria for success.

Middle (6-8)

Planning and carrying out investigations to answer questions or test solutions to problems in 6–8 builds on K–5 experiences and progresses to include investigations that use multiple variables and provide evidence to support explanations or design solutions.

• 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.
• 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.
• Evaluate the accuracy of various methods for collecting data.
• 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.
• Collect data about the performance of a proposed object, tool, process, or system under a range of conditions.

High (9-12)

Planning and carrying out investigations in 9-12 builds on K–8 experiences and progresses to include investigations that provide evidence for and test conceptual, mathematical, physical, and empirical models.

• 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 variables or effects and evaluate the confounding investigation’s design to ensure variables are controlled.
• 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.
• Plan and conduct an investigation or test a design solution in a safe and ethical manner including considerations of environmental, social, and personal impacts.
• Select appropriate tools to collect, record, analyze, and evaluate data.
• Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.
• Manipulate variables and collect data 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.

Students should have opportunities to plan and carry out several different kinds of investigations during their K-12 years. At all levels, they should engage in investigations that range from those structured by the teacher—in order to expose an issue or question that they would be unlikely to explore on their own (e.g., measuring specific properties of materials)—to those that emerge from students’ own questions.

Scientific investigations may be undertaken to describe a phenomenon, or to test a theory or model for how the world works. The purpose of engineering investigations might be to find out how to fix or improve the functioning of a technological system or to compare different solutions to see which best solves a problem. Whether students are doing science or engineering, it is always important for them to state the goal of an investigation, predict outcomes, and plan a course of action that will provide the best evidence to support their conclusions. Students should design investigations that generate data to provide evidence to support claims they make about phenomena. Data are not evidence until used in the process of supporting a claim. Students should use reasoning and scientific ideas, principles, and theories to show why data can be considered evidence.

Over time, students are expected to become more systematic and careful in their methods. In laboratory experiments, students are expected to decide which variables should be treated as results or outputs, which should be treated as inputs and intentionally varied from trial to trial, and which should be controlled, or kept the same across trials. In the case of field observations, planning involves deciding how to collect different samples of data under different conditions, even though not all conditions are under the direct control of the investigator. Planning and carrying out investigations may include elements of all of the other practices.

Scientific investigations produce data that must be analyzed in order to 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.

Primary (K-2)

Analyzing data in K–2 builds on prior experiences and progresses to collecting, recording, and sharing observations.

• Record information (observations, thoughts, and ideas).
• Use and share pictures, drawings, and/or writings of observations.
• Use observations (firsthand or from media) to describe patterns and/or relationships in the natural and designed world(s) in order to answer scientific questions and solve problems.
• Compare predictions (based on prior experiences) to what occurred (observable events).
• Analyze data from tests of an object or tool to determine if it works as intended.

Elementary (3-5)

Analyzing data in 3–5 builds on K–2 experiences and progresses to introducing quantitative approaches to collecting data and conducting multiple trials of qualitative observations. When possible and feasible, digital tools should be used.

• Represent data in tables and/or various graphical displays (bar graphs, pictographs, and/or pie charts) to reveal patterns that indicate relationships.
• Analyze and interpret data to make sense of phenomena, using logical reasoning, mathematics, and/or computation.
• Compare and contrast data collected by different groups in order to discuss similarities and differences in their findings.
• Analyze data to refine a problem statement or the design of a proposed object, tool, or process.
• Use data to evaluate and refine design solutions.

Middle (6-8)

Analyzing data in 6–8 builds on K–5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis.

• Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.
• Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.
• Distinguish between causal and correlational relationships in data.
• Analyze and interpret data to provide evidence for phenomena.
• Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible.
• 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).
• Analyze and interpret data to determine similarities and differences in findings.
• Analyze data to define an optimal operational range for a proposed object, tool, process or system that best meets criteria for success.

High (9-12)

Analyzing data in 9–12 builds on K–8 experiences and progresses to introducing more detailed statistical analysis, the comparison of data sets for consistency, and the use of models to generate and analyze data.

• Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution.
• 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.
• Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data.
• Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.
• Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.
• Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success.

Once collected, data must be presented in a form that can reveal any patterns and relationships and that allows results to be communicated to others. Because raw data as such have little meaning, a major practice of scientists is to organize and interpret data through tabulating, graphing, or statistical analysis. Such analysis can bring out the meaning of data—and their relevance—so that 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 performs, 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.

As students mature, they are expected to expand their capabilities to use a range of tools for tabulation, graphical representation, visualization, and statistical analysis. Students are also expected to improve their abilities to interpret data by identifying significant features and patterns, use mathematics to represent relationships between variables, and take into account sources of error. When possible and feasible, students should use digital tools to analyze and interpret data. Whether analyzing data for the purpose of science or engineering, it is important students present data as evidence to support their conclusions.

In both science and engineering, mathematics and computation are fundamental tools for representing physical variables and their relationships. They are used for a range of tasks such as constructing simulations; statistically analyzing data; and recognizing, expressing, and applying quantitative relationships.

Primary (K-2)

Mathematical and computational thinking at the K–2 level builds on prior experience and progresses to recognizing that mathematics can be used to describe the natural and designed world.

• Decide when to use qualitative vs. quantitative data.
• Use counting and numbers to identify and describe patterns in the natural and designed world(s).
• Describe, measure, and/or compare quantitative attributes of different objects and display the data using simple graphs.
• Use quantitative data to compare two alternative solutions to a problem.

Elementary (3-5)

Mathematical and computational thinking at the 3–5 level builds on K–2 experiences and progresses to extending quantitative measurements to a variety of physical properties and using computation and mathematics to analyze data and compare alternative design solutions.

• Decide if qualitative or quantitative data are best to determine whether a proposed object or tool meets criteria for success.
• Organize simple data sets to reveal patterns that suggest relationships.
• Describe, measure, estimate, and/or graph quantities such as area, volume, weight, and time to address scientific and engineering questions and problems.
• Create and/or use graphs and/or charts generated from simple algorithms to compare alternative solutions to an engineering problem.

Middle (6-8)

Mathematical and computational thinking at the 6–8 level builds on K–5 experiences and progresses to identifying patterns in large data sets and using mathematical concepts to support explanations and arguments.

• Use digital tools (e.g., computers) to analyze very large data sets for patterns and trends.
• Use mathematical representations to describe and/or support scientific conclusions and design solutions.
• Create algorithms (a series of ordered steps) to solve a problem.
• Apply mathematical concepts and/or processes (such as ratio, rate, percent, basic operations, and simple algebra) to scientific and engineering questions and problems.
• Use digital tools and/or mathematical concepts and arguments to test and compare proposed solutions to an engineering design problem.

High (9-12)

Mathematical and computational thinking in 9–12 builds on K–8 experiences and progresses to using algebraic thinking and analysis, a range of linear and nonlinear functions including trigonometric functions, exponential and logarithms, and computational tools for statistical analysis to analyze, represent, and model data. Simple computational simulations are created and used based on mathematical models of basic assumption.

• Create and/or revise a computational model or simulation of a phenomenon, designed device, process, or system.
• Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.
• Apply techniques of algebra and functions to represent and solve scientific and engineering problems.
• 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.
• Apply ratios, rates, percentages, 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.)

Although there are differences in how mathematics and computational thinking are applied in science and in engineering, mathematics often brings these two fields together by enabling engineers to apply the mathematical form of scientific theories and by enabling scientists to use powerful information technologies designed by engineers. Both kinds of professionals can thereby accomplish investigations and analyses and build complex models, which might otherwise be out of the question.

Students are expected to use mathematics to represent physical variables and their relationships, and to make quantitative predictions. Other applications of mathematics in science and engineering include logic, geometry, and at the highest levels, calculus. Computers and digital tools can enhance the power of mathematics by automating calculations, approximating solutions to problems that cannot be calculated precisely, and analyzing large data sets available to identify meaningful patterns. Students are expected to use laboratory tools connected to computers for observing, measuring, recording, and processing data. Students are also expected to engage in computational thinking, which involves strategies for organizing and searching data, creating sequences of steps called algorithms, and using and developing new simulations of natural and designed systems. Mathematics is a tool that is key to understanding science. As such, classroom instruction must include critical skills of mathematics. The ND Science Standards displays many of those skills through the performance expectations, but classroom instruction should enhance all of science through the use of quality mathematical and computational thinking.

The products of science are explanations and the products of engineering are solutions.

Primary (K-2)

Constructing explanations and designing solutions in K–2 builds on prior experiences and progresses to the use of evidence and ideas in constructing evidence-based accounts of natural phenomenon and designing solutions.

• Use information from observations (firsthand and from media) to construct an evidence-based account for natural phenomena.
• Use tools and/or materials to design and/or build a device that solves a specific problem or a solution to a specific problem.
• Generate and/or compare multiple solutions to a problem.

Elementary (3-5)

Constructing explanations and designing solutions in 3–5 builds on K–2 experiences and progresses to the use of evidence in constructing explanations that specify variables that describe and predict phenomena and in designing multiple solutions to design problems.

• Construct an explanation of observed relationships (e.g., the distribution of plants in the back yard).
• Use evidence (e.g., measurements, observations, patterns) to construct or support an explanation or design a solution to a problem.
• Identify the evidence that supports particular points in an explanation.
• Apply scientific ideas to solve design problems.
• Generate and compare multiple solutions to a problem based on how well they meet the criteria and constraints of the design solution.

Middle (6-8)

Constructing explanations and designing solutions in 6–8 builds on K–5 experiences and progresses to include constructing explanations and designing solutions supported by multiple sources of evidence consistent with scientific ideas, principles, and theories.

• Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena. Construct an explanation using models or representations.
• 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.
• Apply scientific ideas, principles, and/or evidence to construct, revise and/or use an explanation for real-world phenomena, examples, or events.
• Apply scientific reasoning to show why the data or evidence is adequate for the explanation or conclusion.
• Apply scientific ideas or principles to design, construct, and/or test a design of an object, tool, process or system.
• Undertake a design project, engaging in the design cycle, to construct and/or implement a solution that meets specific design criteria and constraints.
• Optimize performance of a design by prioritizing criteria, making tradeoffs, testing, revising, and re-testing.

High (9-12)

Constructing explanations and designing solutions in 9–12 builds on K–8 experiences and progresses to explanations and designs that are supported by multiple and independent student-generated sources of evidence consistent with scientific ideas, principles, and theories.

• Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables.
• 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.
• Apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena and solve design problems, taking into account possible unanticipated effects.
• 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.
• 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

The goal of science is to construct explanations for the causes of phenomena. Students are expected to construct their own explanations, as well as apply standard explanations they learn about from their teachers or reading. The Framework states the following about explanation:

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.

An explanation includes a claim that relates how a variable or variables relate to another variable or a set of variables. A claim is often made in response to a question and in the process of answering the question, scientists often design investigations to generate data.

The goal of engineering is to solve problems. Designing solutions to problems is a systematic process that involves defining the problem, then generating, testing, and improving solutions. This practice is described in the Framework as follows.

Asking students to demonstrate their own understanding of the implications of a scientific idea by developing their own explanations of phenomena, whether based on observations they have made or models they have developed, engages them in an essential part of the process by which conceptual change can occur.

In engineering, the goal is a design rather than an explanation. The process of developing a design is iterative and systematic, as is the process of developing an explanation or a theory in science. Engineers’ activities, however, have elements that are distinct from those of scientists. These elements include specifying constraints and criteria for desired qualities of the solution, developing a design plan, producing and testing models or prototypes, selecting among alternative design features to optimize the achievement of design criteria, and refining design ideas based on the performance of a prototype or simulation.

Argumentation is the process by which explanations and solutions are reached.

Primary (K-2)

Engaging in argument from evidence in K–2 builds on prior experiences and progresses to comparing ideas and representations about the natural and designed world(s).

• Identify arguments that are supported by evidence.
• Distinguish between explanations that account for all gathered evidence and those that do not.
• Analyze why some evidence is relevant to a scientific question and some is not.
• Distinguish between opinions and evidence in one’s own explanations.
• Listen actively to arguments to indicate agreement or disagreement based on evidence, and/or to retell the main points of the argument.
• Construct an argument with evidence to support a claim.
• Make a claim about the effectiveness of an object, tool, or solution that is supported by relevant evidence.

Elementary (3-5)

Engaging in argument from evidence in 3–5 builds on K–2 experiences and progresses to critiquing the scientific explanations or solutions proposed by peers by citing relevant evidence about the natural and designed world(s).

• Compare and refine arguments based on an evaluation of the evidence presented.
• Distinguish among facts, reasoned judgment based on research findings, and speculation in an explanation.
• Respectfully provide and receive critiques from peers about a proposed procedure, explanation or model by citing relevant evidence and posing specific questions.
• Construct and/or support an argument with evidence, data, and/or a model.
• Use data to evaluate claims about cause and effect.
• Make a claim about the merit of a solution to a problem by citing relevant evidence about how it meets the criteria and constraints of the problem.

Middle (6-8)

Engaging in argument from evidence in 6–8 builds on K–5 experiences and progresses to constructing a convincing argument that supports or refutes claims for either explanations or solutions about the natural and designed world(s).

• Compare and critique two arguments on the same topic and analyze whether they emphasize similar or different evidence and/or interpretations of facts.
• 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.
• 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.
• 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.
• Evaluate competing design solutions based on jointly developed and agreed-upon design criteria.

High (9-12)

Engaging in argument from evidence in 9–12 builds on K–8 experiences and progresses to using appropriate and sufficient evidence and scientific reasoning to defend and critique claims and explanations about the natural and designed world(s). Arguments may also come from current scientific or historical episodes in science.

• 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.
• Evaluate the claims, evidence, and/or reasoning behind currently accepted explanations or solutions to determine the merits of arguments.
• Respectfully provide and/or receive critiques on scientific arguments by probing reasoning and evidence and challenging ideas and conclusions, responding thoughtfully to diverse perspectives, and determining what additional information is required to resolve contradictions.
• Construct, use, and/or present an oral and written argument or counter-arguments based on data and evidence.
• 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.
• Evaluate competing design solutions to a real-world problem based on scientific ideas and principles, empirical evidence, and logical arguments regarding relevant factors (e.g. economic, societal, environmental, ethical considerations).

The study of science and engineering should produce a sense of the process of argument necessary for advancing and defending a new idea or an explanation of a phenomenon and the norms for conducting such arguments. In that spirit, students should argue for the explanations they construct, defend their interpretations of the associated data, and advocate for the designs they propose.

Argumentation is a process for reaching agreements about explanations and design solutions. In science, reasoning and argument based on evidence are essential in identifying the best explanation for a natural phenomenon. In engineering, reasoning and argument are needed to identify the best solution to a design problem. Student engagement in scientific argumentation is critical if students are to understand the culture in which scientists live, and how to apply science and engineering for the benefit of society. As such, argument is a process based on evidence and reasoning that leads to explanations acceptable by the scientific community and design solutions acceptable by the engineering community.

Argument in science goes beyond reaching agreements in explanations and design solutions. Whether investigating a phenomenon, testing a design, or constructing a model to provide a mechanism for an explanation, students are expected to use argumentation to listen to, compare, and evaluate competing ideas and methods based on their merits. Scientists and engineers engage in argumentation when investigating a phenomenon, testing a design solution, resolving questions about measurements, building data models, and using evidence to evaluate claims.

Scientists and engineers must be able to communicate clearly and persuasively the ideas and methods they generate. Critiquing and communicating ideas individually and in groups is a critical professional activity.

Primary (K-2)

Obtaining, evaluating, and communicating information in K–2 builds on prior experiences and uses observations and texts to communicate new information.

• Read grade-appropriate texts and/or use media to obtain scientific and/or technical information to determine patterns in and/or evidence about the natural and designed world(s).
• Describe how specific images (e.g., a diagram showing how a machine works) support a scientific or engineering idea.
• Obtain information using various texts, text features (e.g., headings, tables of contents, glossaries, electronic menus, icons), and other media that will be useful in answering a scientific question and/or supporting a scientific claim.
• Communicate information or design ideas and/or solutions with others in oral and/or written forms using models, drawings, writing, or numbers that provide detail about scientific ideas, practices, and/or design ideas.

Elementary (3-5)

Obtaining, evaluating, and communicating information in 3–5 builds on K–2 experiences and progresses to evaluating the merit and accuracy of ideas and methods.

• Obtain and combine information from books and other reliable media to explain phenomena.
• Read and comprehend grade-appropriate complex texts and/or other reliable media to summarize and obtain scientific and technical ideas and describe how they are supported by evidence.
• Compare and/or combine across complex texts and/or other reliable media to support the engagement in other scientific and/or engineering practices.
• Combine information in written text with that contained in corresponding tables, diagrams, and/or charts to support the engagement in other scientific and/or engineering practices.
• Obtain and combine information from books and/or other reliable media to explain phenomena or solutions to a design problem.
• Communicate scientific and/or technical information orally and/or in written formats, including various forms of media and may include tables, diagrams, and charts.

Middle (6-8)

Obtaining, evaluating, and communicating information in 6–8 builds on K–5 experiences and progresses to evaluating the merit and validity of ideas and methods.

• Critically read scientific texts adapted for classroom use to determine the central ideas and/or obtain scientific and/or technical information to describe patterns in and/or evidence about the natural and designed world(s).
• Integrate qualitative and/or quantitative scientific and/or technical information in written text with that contained in media and visual displays to clarify claims and findings.
• Gather, read, synthesize information from multiple appropriate sources and assess the credibility, accuracy, and possible bias of each publication and methods used, and describe how they are supported or not supported by evidence.
• Evaluate data, hypotheses, and/or conclusions in scientific and technical texts in light of competing information or accounts.
• Communicate scientific and/or technical information (e.g. about a proposed object, tool, process, system) in writing and/or through oral presentations.

High (9-12)

Obtaining, evaluating, and communicating information in 9–12 builds on K–8 experiences and progresses to evaluating the validity and reliability of the claims, methods, and designs.

• Critically read scientific literature adapted for classroom use to determine the central ideas or conclusions and/or to obtain scientific and/or technical information to summarize complex evidence, concepts, processes, or information presented in a text by paraphrasing them in simpler but still accurate terms.
• Compare, integrate and evaluate sources of information presented in different media or formats (e.g., visually, quantitatively) as well as in words in order to address a scientific question or solve a problem.
• Gather, read, and evaluate scientific and/or technical information from multiple authoritative sources, assessing the evidence and usefulness of each source.
• Evaluate the validity and reliability of and/or synthesize multiple claims, methods, and/or designs that appear in scientific and technical texts or media reports, verifying the data when possible.
• Communicate scientific and/or technical information or ideas (e.g. about phenomena and/or the process of development and the design and performance of a proposed process or system) in multiple formats (including orally, graphically, textually, and mathematically).

Any education in science and engineering needs to develop students’ ability to read and produce domain-specific text. As such, every science or engineering lesson is in part a language lesson, particularly reading and producing the genres of texts that are intrinsic to science and engineering.

Being able to read, interpret, and produce scientific and technical text is a fundamental practice of science and engineering, as is the ability to communicate clearly and persuasively. Being a critical consumer of information about science and engineering requires the ability to read or view reports of scientific or technological advances or applications (whether found in the press, or the Internet, or in a town meeting) and to recognize the salient ideas, identify sources of error and methodological flaws, distinguish observations from inferences, arguments from explanations, and claims from evidence. Scientists and engineers employ multiple sources to obtain information used to evaluate the merit and validity of claims, methods, and designs. Communicating information, evidence, and ideas can be done in multiple ways: using tables, diagrams, graphs, models, interactive displays, and equations as well as orally, in writing, and through extended discussions.

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