Frequently Asked Questions
In our work with teachers and instructional leaders, we have encountered a number of common questions about the project and the science practices. Below are our answers to these concerns. If you still have questions, comments, or feedback, please contact us.
GROUPING OF PRACTICES
Why are the eight science practices grouped into investigating, sensemaking and critiquing practices?
Through our work with teachers, we have found that thinking of the science practices as distinct can be challenging, particularly for those who are less familiar with the Next Generation Science Standards. Instead, we find it useful to think of the practices in relation to three interrelated categories: (1) Investigating Practices, (2) Sensemaking Practices, and (3) Critiquing Practices. The Investigating Practices focus on asking questions and investigating the natural world. The products of these investigations are data. The Sensemaking Practices focus on analyzing data by looking for patterns and relationships to develop explanations and models. The Critiquing Practices emphasize that students need to compare, contrast, and evaluate competing explanations and models as they make sense of the world around them (McNeill, Katsh-Singer, & Pelletier, 2015). Beginning with three categories instead of eight distinct practices can be a less overwhelming introduction for teachers.
Through our work with teachers, we have found that thinking of the science practices as distinct can be challenging, particularly for those who are less familiar with the Next Generation Science Standards. Instead, we find it useful to think of the practices in relation to three interrelated categories: (1) Investigating Practices, (2) Sensemaking Practices, and (3) Critiquing Practices. The Investigating Practices focus on asking questions and investigating the natural world. The products of these investigations are data. The Sensemaking Practices focus on analyzing data by looking for patterns and relationships to develop explanations and models. The Critiquing Practices emphasize that students need to compare, contrast, and evaluate competing explanations and models as they make sense of the world around them (McNeill, Katsh-Singer, & Pelletier, 2015). Beginning with three categories instead of eight distinct practices can be a less overwhelming introduction for teachers.
Number of Practices in a Lesson
Should teachers engage students in multiple science practices in one lesson?
It depends! Teachers may find that a particular lesson is suited to fostering student engagement in more than one science practice; however, this does not suggest that teachers should incorporate as many practices as possible into each lesson. More important than the number of science practices present in a given lesson is the level in which the practices are found along the Continuum. In alignment with the Continuum, teachers should foster a classroom culture that prioritizes student engagement in science practices that are: student directed and collaborative, connected to the natural world, focused on scientific evidence, and informed by critique. In a more long-term sense, teachers should provide students with opportunities to engage in Investigating, Sensemaking, and Critiquing Practices over the course of a unit.
It depends! Teachers may find that a particular lesson is suited to fostering student engagement in more than one science practice; however, this does not suggest that teachers should incorporate as many practices as possible into each lesson. More important than the number of science practices present in a given lesson is the level in which the practices are found along the Continuum. In alignment with the Continuum, teachers should foster a classroom culture that prioritizes student engagement in science practices that are: student directed and collaborative, connected to the natural world, focused on scientific evidence, and informed by critique. In a more long-term sense, teachers should provide students with opportunities to engage in Investigating, Sensemaking, and Critiquing Practices over the course of a unit.
The Continuum across grade levels
How do the levels of the Continuum for each practice differ at various grades? (Why isn’t the continuum grade-specific?)
The Continuum was written to provide a description of each science practice at four increasingly sophisticated levels, which are not grade specific. Teachers of K-8 students can teach in developmentally appropriate ways at any of these levels. With this in mind, students – across all grade levels—are able to engage in the science practices at the highest levels of the Continuum. However, student engagement in science practices will look different depending on the science ideas (i.e. disciplinary core ideas) at a particular grade level. For example, a level four on the Continuum for a given practice will look different in first grade classroom when compared to an eighth grade classroom due to different phenomena and science ideas (i.e. disciplinary core ideas).
The Continuum was written to provide a description of each science practice at four increasingly sophisticated levels, which are not grade specific. Teachers of K-8 students can teach in developmentally appropriate ways at any of these levels. With this in mind, students – across all grade levels—are able to engage in the science practices at the highest levels of the Continuum. However, student engagement in science practices will look different depending on the science ideas (i.e. disciplinary core ideas) at a particular grade level. For example, a level four on the Continuum for a given practice will look different in first grade classroom when compared to an eighth grade classroom due to different phenomena and science ideas (i.e. disciplinary core ideas).
inquiry vs. Science Practices
What is “scientific inquiry”? Why is the phrase not used in NGSS?
In the past, there has been great emphasis on this idea of “scientific inquiry,” and making sure that lessons are “inquiry-based.” The writers of NGSS chose to move away from the term inquiry because it was too vague and interpreted by many people to mean different things. Instead, the science practices more specifically define what it looks like to think and act like a scientist. These more concrete definitions make it easier for teachers and principals to see when students are engaging in the practices. We believe that lessons that require students to truly engage in these practices may look like what some people called “inquiry-based” lessons in the past. However, some lessons that would have been previously defined as “inquiry” do not align with the science practices.
In the past, there has been great emphasis on this idea of “scientific inquiry,” and making sure that lessons are “inquiry-based.” The writers of NGSS chose to move away from the term inquiry because it was too vague and interpreted by many people to mean different things. Instead, the science practices more specifically define what it looks like to think and act like a scientist. These more concrete definitions make it easier for teachers and principals to see when students are engaging in the practices. We believe that lessons that require students to truly engage in these practices may look like what some people called “inquiry-based” lessons in the past. However, some lessons that would have been previously defined as “inquiry” do not align with the science practices.
Science practices vs. Other disciplines
Are the science practices similar to the ELA and math practices?
In a word, yes! The science and engineering practices represent the ways of thinking and working that are most common among scientists. While some of them are unique to science, many of the ways an expert scientist works are similar to the ways an adept mathematician or literary thinker does. The Understanding Language Initiative at Stanford University has a helpful diagram of the overlaps between the science and engineering practices, the Common Core math practices, and the Common Core English Language Arts practices. For example, constructing arguments cuts across all three subjects but planning and carrying out investigations is unique to science. We hope this diagram helps make clear that in working on developing students’ skill with the science and engineering practices, teachers can also help students develop in ELA and math.
In a word, yes! The science and engineering practices represent the ways of thinking and working that are most common among scientists. While some of them are unique to science, many of the ways an expert scientist works are similar to the ways an adept mathematician or literary thinker does. The Understanding Language Initiative at Stanford University has a helpful diagram of the overlaps between the science and engineering practices, the Common Core math practices, and the Common Core English Language Arts practices. For example, constructing arguments cuts across all three subjects but planning and carrying out investigations is unique to science. We hope this diagram helps make clear that in working on developing students’ skill with the science and engineering practices, teachers can also help students develop in ELA and math.
Asking questions in Science vs. Other Disciplines
How is asking questions in science different than asking questions in other disciplines?
The practice of asking questions is valuable in all disciplines, however asking scientific questions is different from asking question in other subjects. In science, the practice of asking questions leads to descriptions and explanations of how the natural world works. Scientific questions are distinguished from questions in other disciplines in that the answers lie in explanations supported by empirical evidence, including evidence gathered by others or through investigation. For example, “how do air pollutants affect plant growth?” is a scientific question because it can be answered using evidence from an investigation. But “what are air pollutants?” is not a scientific question because it is answered using factual information rather than empirical evidence.
The practice of asking questions is valuable in all disciplines, however asking scientific questions is different from asking question in other subjects. In science, the practice of asking questions leads to descriptions and explanations of how the natural world works. Scientific questions are distinguished from questions in other disciplines in that the answers lie in explanations supported by empirical evidence, including evidence gathered by others or through investigation. For example, “how do air pollutants affect plant growth?” is a scientific question because it can be answered using evidence from an investigation. But “what are air pollutants?” is not a scientific question because it is answered using factual information rather than empirical evidence.
Argumentation in Science vs. Other Disciplines
How is scientific argumentation different than argumentation in other disciplines?
Scientific argumentation is similar to argumentation in other disciplines in terms of argument structure. Both scientific and non-scientific arguments can be constructed using the claim, evidence and reasoning (CER) framework. However, scientific and non-scientific arguments differ in how they use the CER framework. In scientific arguments, a claim is supported by evidence in the form of data (i.e. observations, measurements, etc.). Reasoning then explains why the evidence supports the claim using scientific ideas or principles. In arguments from other disciplines, a claim is supported by different evidence. This evidence is often based in instances from text, facts or other information rather than in scientific data. Reasoning still explains why the evidence supports the claim, but the justification can look different (e.g. literary ideas and principles, personal opinions, beliefs, and ethics).
Scientific argumentation is similar to argumentation in other disciplines in terms of argument structure. Both scientific and non-scientific arguments can be constructed using the claim, evidence and reasoning (CER) framework. However, scientific and non-scientific arguments differ in how they use the CER framework. In scientific arguments, a claim is supported by evidence in the form of data (i.e. observations, measurements, etc.). Reasoning then explains why the evidence supports the claim using scientific ideas or principles. In arguments from other disciplines, a claim is supported by different evidence. This evidence is often based in instances from text, facts or other information rather than in scientific data. Reasoning still explains why the evidence supports the claim, but the justification can look different (e.g. literary ideas and principles, personal opinions, beliefs, and ethics).
Explanation vs. Argument
What is the difference between a scientific explanation and scientific argument?
It can be hard to distinguish between explanation and argumentation because these are complementary practices that the scientific community uses to build knowledge. Although the two practices are deeply linked to each other, they actually do different intellectual work for scientists. A scientific explanation is an explanatory account that articulates how or why a natural phenomenon occurs. Scientific explanations are supported by evidence and scientific ideas. The practice of scientific explanation involves sensemaking, or knowledge construction, as scientists are trying to build knowledge regarding how or why phenomena occur. Scientific argumentation is a process that occurs when there are multiple ideas or claims to discuss and reconcile. An argument includes a claim supported by evidence and reasoning. It also evaluates and critiques competing claims. The practice of scientific argumentation involves persuasion, in which scientists construct and debate claims using evidence and reasoning. Scientists seek to convince their peers of the quality of the explanation, using evidence.
It can be hard to distinguish between explanation and argumentation because these are complementary practices that the scientific community uses to build knowledge. Although the two practices are deeply linked to each other, they actually do different intellectual work for scientists. A scientific explanation is an explanatory account that articulates how or why a natural phenomenon occurs. Scientific explanations are supported by evidence and scientific ideas. The practice of scientific explanation involves sensemaking, or knowledge construction, as scientists are trying to build knowledge regarding how or why phenomena occur. Scientific argumentation is a process that occurs when there are multiple ideas or claims to discuss and reconcile. An argument includes a claim supported by evidence and reasoning. It also evaluates and critiques competing claims. The practice of scientific argumentation involves persuasion, in which scientists construct and debate claims using evidence and reasoning. Scientists seek to convince their peers of the quality of the explanation, using evidence.
The C-E-R Framework
Can the claim, evidence, and reasoning framework be used for constructing explanations and engaging in argument from evidence?
Yes, it can! The claim, evidence, reasoning framework is used for both scientific explanations and arguments. The only structural difference between an explanation and an argument involves the claim portion of the framework. In a scientific explanation, the claim is always an explanatory account that describes how or why a phenomenon occurs. In a scientific argument, the claim answers a question or problem more broadly and therefore can be something other than an explanatory account (i.e. model, design solution, investigatory methods, etc.).
Yes, it can! The claim, evidence, reasoning framework is used for both scientific explanations and arguments. The only structural difference between an explanation and an argument involves the claim portion of the framework. In a scientific explanation, the claim is always an explanatory account that describes how or why a phenomenon occurs. In a scientific argument, the claim answers a question or problem more broadly and therefore can be something other than an explanatory account (i.e. model, design solution, investigatory methods, etc.).
Data vs. Evidence
What is the difference between data and evidence?
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During an investigation, scientists collect a lot of data. These data can be qualitative, like observations and descriptions, or quantitative, like measurements. Not all, data, however, is useful in constructing explanations about the world or creating scientific arguments. Only the data that is helpful in supporting a claim is evidence in explanations or arguments. You can imagine this relationship like a bulls-eye: all evidence is data but not all data is evidence.
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Using math and computational thinking vs. other practices
How is the using mathematics and computational thinking practice different from the skills used in other science practices (e.g. planning and carrying out investigations, analyzing and interpreting data)?
Mathematical and computational thinking is used for a range of tasks such as measurement, data organization (i.e. graphs or charts), mathematical computation (e.g., such as ratio, rate, percent, basic operations, and simple algebra), and in the construction of simulations. These tasks are critical to the investigation, modeling, and analysis practices, as students are expected to represent physical variables and their relationships, to express quantitative relationships, and to statistically analyze data. The practice of using mathematical and computational thinking is therefore not distinct from the skills used in other science practices. As result, the mathematical and computational thinking practice will typically occur with another practice in a science lesson.
Mathematical and computational thinking is used for a range of tasks such as measurement, data organization (i.e. graphs or charts), mathematical computation (e.g., such as ratio, rate, percent, basic operations, and simple algebra), and in the construction of simulations. These tasks are critical to the investigation, modeling, and analysis practices, as students are expected to represent physical variables and their relationships, to express quantitative relationships, and to statistically analyze data. The practice of using mathematical and computational thinking is therefore not distinct from the skills used in other science practices. As result, the mathematical and computational thinking practice will typically occur with another practice in a science lesson.
Models in science
What is a model? How do you know if something counts as a model?
The concept of a model can sometimes be a little fuzzy! A model is an abstract representation of phenomena. Models can predict or explain the world. In other words, models are approximations of objects, phenomena, and systems, but not the real thing. Models can be represented as diagrams, 3-D objects, mathematical representations, analogies or computer simulations. They can be used in a few different ways: to help us develop questions and explanations, to generate data that we can use to make predictions, and to help us communicate ideas to others.
The concept of a model can sometimes be a little fuzzy! A model is an abstract representation of phenomena. Models can predict or explain the world. In other words, models are approximations of objects, phenomena, and systems, but not the real thing. Models can be represented as diagrams, 3-D objects, mathematical representations, analogies or computer simulations. They can be used in a few different ways: to help us develop questions and explanations, to generate data that we can use to make predictions, and to help us communicate ideas to others.
Scientific Models vs. investigations
How is the developing and using models practice different from the planning and carrying out investigation practice? Can a model be used in an investigation?
It can sometimes be hard to tell the difference between models and investigations because both can be used to describe phenomena. Models are abstract representations of phenomena that are used as tools to predict or explain the world. An investigation is a systematic way to gather data about the natural world either in the field or in a laboratory setting. The difference between a model and an investigation is that a model is an abstract representation (diagrams, 3-D objects, etc.) of phenomena whereas an investigation involves a physical representation (actual instances) of phenomena. Models can be incorporated into investigations since some investigations test explanatory models of the world and the models’ predictions. In that case, the investigation would determine if the models’ predictions are supported by data.
It can sometimes be hard to tell the difference between models and investigations because both can be used to describe phenomena. Models are abstract representations of phenomena that are used as tools to predict or explain the world. An investigation is a systematic way to gather data about the natural world either in the field or in a laboratory setting. The difference between a model and an investigation is that a model is an abstract representation (diagrams, 3-D objects, etc.) of phenomena whereas an investigation involves a physical representation (actual instances) of phenomena. Models can be incorporated into investigations since some investigations test explanatory models of the world and the models’ predictions. In that case, the investigation would determine if the models’ predictions are supported by data.
Scientific Models vs. Engineering
How are models different than engineering design?
Models are sometimes confused with engineering design tasks, but these are two different activities. Engineering design tasks involve defining problems and designing solutions. An example would be if students are given a problem: they need to cook food using thermal energy. In this case, the student might design a solar cooker to capture the sun’s energy to cook food, which would be a solution to the problem. Models do not involve designing solutions to problems, but rather focus on predicting or explaining the natural world. An example would be students developing food webs to explain how energy flows through an ecosystem.
Models are sometimes confused with engineering design tasks, but these are two different activities. Engineering design tasks involve defining problems and designing solutions. An example would be if students are given a problem: they need to cook food using thermal energy. In this case, the student might design a solar cooker to capture the sun’s energy to cook food, which would be a solution to the problem. Models do not involve designing solutions to problems, but rather focus on predicting or explaining the natural world. An example would be students developing food webs to explain how energy flows through an ecosystem.
Definition of Text
What counts as a “text” for the "obtaining, evaluating and communicating information" practice?
SEP 8 asks students to obtain and evaluate information from a variety of texts as well as communicate it effectively to others. A classroom that asks students to engage in this practice effectively is one where the teacher (or textbook) is not the only, or even primary, source of information. Many people talk about these sources of information as “texts,” but in this context any of a wide variety of sources of information can count as a text. The National Research Council defines a text in science as “any form of communication, from printed text to video productions,” so students do not have to be reading written words to engage in this practice.
SEP 8 asks students to obtain and evaluate information from a variety of texts as well as communicate it effectively to others. A classroom that asks students to engage in this practice effectively is one where the teacher (or textbook) is not the only, or even primary, source of information. Many people talk about these sources of information as “texts,” but in this context any of a wide variety of sources of information can count as a text. The National Research Council defines a text in science as “any form of communication, from printed text to video productions,” so students do not have to be reading written words to engage in this practice.
Definition of Phenomenon
What is a phenomenon in science? Why is it important to NGSS?
“Natural phenomena are observable events that occur in the universe and that we can use our science knowledge to explain or predict. The goal of building knowledge in science is to develop general ideas, based on evidence, that can explain and predict phenomena” (NGSS). Although phenomena play a fundamental role in science, classroom instruction often focuses on teaching the products of science (i.e. facts, formulas, laws, theories) as disconnected from observable real-world events. In a phenomena-centered classroom, students figure out why or how something happens rather than solely learning about a topic (NGSS). In this context, students are able to understand real-world phenomena while also developing deeper content knowledge. Read more about the importance of phenomena in the NGSS here: Using Phenomena in NGSS-Designed Lessons and Units
“Natural phenomena are observable events that occur in the universe and that we can use our science knowledge to explain or predict. The goal of building knowledge in science is to develop general ideas, based on evidence, that can explain and predict phenomena” (NGSS). Although phenomena play a fundamental role in science, classroom instruction often focuses on teaching the products of science (i.e. facts, formulas, laws, theories) as disconnected from observable real-world events. In a phenomena-centered classroom, students figure out why or how something happens rather than solely learning about a topic (NGSS). In this context, students are able to understand real-world phenomena while also developing deeper content knowledge. Read more about the importance of phenomena in the NGSS here: Using Phenomena in NGSS-Designed Lessons and Units