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Learning Orientation

Emphasize learning and understanding and de-emphasize grades, competition, and social comparison

Learning Orientation NGSS Connections

NGSS Connections

In this section, we first explain the synergy between this MDP and the eight science and engineering practices, then provide examples, options, and variations of activities and instructional strategies that are aligned with this MDP for each science and engineering practice. However, this does not mean that teachers must use all of these strategies to enact this MDP when promoting the science and engineering practice, nor that these strategies are the only way to do so. We encourage teachers to use their professional discretion to select what will work best for them and their classrooms, and to modify and innovate on these strategies.
Practice 1: Asking Questions and Defining Problems

Asking questions and defining problems drives science and engineering. A curiosity to figure out a phenomenon or solve a problem drives many of the decisions scientists and engineers make. Having a learning orientation rather than striving to complete assignments, earn points, outperform others, or try to “look smart” supports authentic scientific inquiry and engineering design. Instructional supports for a learning orientation are also necessary to ensure that students feel comfortable asking questions, as ego-oriented students or students who are concerned about confirming negative ability stereotypes could view questions as evidence of incompetence [see Motivation as a Tool for Equity]. Scientists and engineers ask specific types of questions, and as students learn to ask these types of questions, they will make mistakes. A learning orientation will help students to focus on their growth in this skill rather than view themselves as a failure when they make mistakes as they learn.


Explicitly teach students about different categories of scientific questions and the different kinds of information they yield (e.g., descriptive questions to collect evidence, clarification questions, generative investigative questions) and provide them with question stems for each type. Provide numerous opportunities for students to practice generating these different types of scientific questions for different purposes to set the expectation that students are responsible for asking questions to build scientific knowledge.
Create structures/practices in the classroom that provide opportunities for students to pose scientific questions that drive learning. This helps remind students that the overall purpose of their endeavors in science class is to develop a greater understanding of phenomena. For example:
  • Use a Driving Question Board: Have students list what they are curious about regarding a phenomenon or what interests them, and then use that to generate scientific questions that can be investigated. Post the question(s) the students are trying to answer and consistently return to them throughout the unit, asking the class what questions have been answered and what new questions have arisen along the way
  • A KWL graphic organizer is another way to encourage question-asking. After identifying prior knowledge in the “Know” column, students can pose scientific questions for the “Wonder” column and see that their questions are central to the process of increasing/developing knowledge
  • During investigations or at the beginning of units, conduct anonymous live polling where students can both pose scientific questions and see what questions other students are asking. This will help students see that asking questions is a normal part of science inquiry
  • Maintain a “parking lot” for students to place questions that arise to them during class. Regularly read those questions to the class, discuss the extent to which they are scientific and help them to understand phenomena, and incorporate them into instruction as appropriate
Do a think-aloud in which the teacher models scientific question-asking about a phenomenon or models defining problems, and/or how questions lead to other science and engineering practices, such as analyzing data or planning and carrying out investigations. Eventually, once this routine is familiar, students could also be asked to do a think-aloud of their process.
Incorporate scientific question-asking as an active reading strategy to normalize the practice of asking scientific and engineering questions as part of the process of developing understanding of phenomena or solving problems.
To show the value of asking scientific questions, design activities that use questions from the Driving Question Board. For example:
  • Take a scientific question off of the board and say to the class, “I think we can answer this one now,” and use the question for formative or summative purposes
  • Different scientific questions can be taken down from the DQB and given to different groups of students to answer collaboratively. These questions can be posed to the class, and students can choose one to answer, writing an explanation that uses evidence from class activities, readings, and what they have figured out thus far
  • Students can be invited or assigned to pursue scientific questions independently and to present them to peers or to create a booklet to teach a younger student about what they want to know about a phenomenon or design problem

Models help make thinking/understanding visible to oneself and to others, which supports the development and revision of scientific ideas. There are numerous ways to develop representations of the same phenomenon or design problem, which can raise important questions and clarifications; developing a model is not about producing the one “right” representation. Instructional supports for a learning orientation help students adopt these perspectives. Additionally, models should be evaluated and revised over time as understanding develops. A learning orientation supports this kind of ongoing evaluation and revision of models and scientific ideas: with a learning orientation, early/naive models are not “wrong;” they are steps in the process of gaining understanding.


Frame the purpose of model creation as helping us to understand why something behaves the way it does or predicting what will happen, rather than being just an assignment to complete. Emphasize that by grappling with the delineation of the system being modeled, its components, and their interactions, students can explore and build upon their current understanding of a phenomenon or design problem and identify areas to explore further.
Have students brainstorm possible models, representations, and relationships to produce as many ideas as possible. Keep copies of earlier models so that students have a visual record of different options and changes in thinking over time.
Do a gallery walk or other share-out with structure (e.g., sentence stems or a note-taking guide) to help students observe and reflect on how peers’ models are different without judging which one is “best”/“right.” Conclude by asking students to reflect on what they’ve learned/how their own understanding has changed/what new questions they have after observing others’ models/how they might revise their model.
Have students provide feedback on their peers’ models by adding comments to sticky notes and placing these sticky notes on the models. By providing focused commentary on how their peers can add an idea or revise an idea in their models, or by posing a question, students become critiquers of science ideas. Also, adding to, revising, or questioning ideas supports the idea that models are not static, but can and should be revised based on evidence and reasoning as students make sense of phenomena or solve problems.
When students are developing a model, incorporate space (e.g., explicit prompts and class time to respond to them) for students to explain their thinking. Discuss affordances and limitations of different types or components of models (in what situations you might use different models/model components) so that students understand modeling choices as a matter of utility/appropriateness vs. being right or wrong. Emphasize understanding by having students explain how components of a model relate to one another, interact over time, and contribute to understanding a phenomenon or designing solutions to problems.
Create a parking lot so that students can post questions on models they are actively using in class. Students can return to this to see what questions they have answered and if new questions have risen as a result of learning more about the phenomenon they are investigating or the design problem they are solving.
Have individual students record their developing ideas in their science notebooks so that they are continually revisiting and revising their models as they develop deeper understanding of a phenomenon or determine an optimal solution to a problem over time.

Supporting a learning orientation helps to place the emphasis on the goal of an investigation (i.e., What are we trying to figure out?), rather than casting it as merely a set of steps to complete or a way to learn a science fact. When planning investigations, an emphasis on the goal of the investigation supports students in making an investigation plan that will best achieve that goal. Framing a prediction as a best guess for right now based on available evidence and/or prior learning, and emphasizing that we update our understanding of a phenomenon or which design solution best meets the criteria and constraints of a problem as we gather more evidence are important strategies to help students students engage in making predictions as part of a learning process, rather than worrying about how their predictions will be judged by their classmates. Especially for students who do not have much experience planning and carrying out investigations, it is common to make errors during investigations and/or to obtain unexpected results. With a learning orientation, students will view those errors as a part of their own learning, as well as part of the process of doing science.


Frame investigations as a safe place to fail and talk to students about what scientists have learned from “failed” experiments/investigations in the past. If the students’ own investigation “doesn’t work,” again normalize the idea of “failed” experiments in science - “as scientists, where do we go from here?”
Begin investigations with a discussion of the scientific purpose for the investigation. For investigations that students may be mostly executing as written, invite students to examine the materials and procedures and explain how they will help investigate the phenomenon or solve a problem. For investigations that students are planning and carrying out on their own, invite students to generate procedures in groups and share out their ideas so that the class can see multiple options for achieving the same scientific objective.
Provide a set of guiding questions for creating and carrying out a successful investigation that prompt students to think through their design choices. Have students record these questions in their science notebooks. Use either SI units or non-metric units of measurement as appropriate for the investigation. Possible questions could include:
  • Is this phenomenon something you could observe occurring naturally or should you do something in the classroom to explore it (i.e., a controlled experiment)?
  • What evidence would you need to answer your question?
  • What equipment do you need to do this?
  • How will you know if you have been successful?
  • For observational investigations:
    • What would you need to observe to answer your question?
  • For a controlled experiment:
    • Which variables will be treated as the outcomes of the investigation?
    • How can you measure what you think is important?
    • Which conditions would you vary to see if they have any effect on the outcome variable?
    • What are all the other variables or conditions that should be held constant during the investigation?
During the planning and carrying out of investigations, pause the class periodically to discuss progress and challenges as they figure out a phenomenon or design solutions to a problem. Prompt students to explain procedures that are working well and those that are not and why those procedures may have limitations. Encourage students to learn from each other. Frame progress as the result of student effort and strategy use and frame challenges as learning opportunities.
Regularly conduct post-investigation debriefs about why an investigation did or didn’t “work.” Help students focus on the effectiveness of design choices and strategies, and possible revisions (e.g., “what can we learn from that? What modifications might we make next time?”). Based on this debrief discussion, allow students to redo their investigation and apply their more sophisticated knowledge to this replication effort. In addition, invite students to generate ideas for a class poster or other resource that will remind students of the best practices they have learned for planning and carrying out future investigations.
Provide a rubric for an investigation that includes the many aspects of the investigation (e.g., procedure, data table, data collection, measurement, teamwork, etc.). Model for students how to use a rubric to understand an assignment so that students can understand the purpose of the investigation and focus on their progress as a result of their effort and effective strategy use.

Data collection, especially by young scientists and engineers with limited experience, can contain a large amount of error. During analysis, having a learning orientation will help frame that error as a critical part of the learning experience (both learning techniques for how to reduce the error in future data collection and learning how to account for error in data interpretation) rather than a failure. Supporting a learning orientation will also help with encouraging students to engage deeply with their data to make sense of a phenomenon or design solutions to design problems, rather than merely performing calculations or getting the “right” answer.


Ask students to identify what patterns they see in a data set and develop their own hypotheses about what that pattern can tell them about evidence for other phenomena (e.g, the forces exerted by a rocket can inform you about the forces of other engine-propelled devices).
Engage students in error analysis to figure out what went wrong during data collection, where errors were made (including if there was uncertainty in measurement) and how these errors are reflected in the data, and why different students or different lab groups may have obtained discrepant results. Emphasize that making errors is a normal part of learning how to make precise and accurate measurements and that, even when you have developed those skills, there will always be error in your measurements (e.g., estimating to the nearest tenth of a millimeter on a ruler with millimeter hash marks).
Model and then scaffold how to judge the appropriateness and correctness of data analysis and interpretation. For example, design data analysis questions or assessments such that they include an opportunity for students to explain the thinking behind their analyses/interpretations. Provide feedback and/or evaluate these responses based on the skills students demonstrate and their reasoning and evidence, rather than just the percent of correct/incorrect answers.
When the teacher makes a mistake in a computation, model a response that frames the mistake as normal and a learning opportunity, rather than becoming defensive about the error.
Use think-alouds to model a learning orientation to students; they can be used to normalize struggle, confusion, and mistakes and to model effective strategies for analyzing and interpreting data.
When discussing the interpretation of data, use the Learning Orientation Talk Moves or resources like the Accountable Talk Sourcebook, the “Supporting Discussions” chapter of the Open SciEd Teacher Handbook, Talk Science Primer, and Discourse Primer for Science Teachers to elicit multiple student perspectives before concluding which interpretations are supported by the data and to encourage students to build on each other’s ideas, critique each other respectfully, and acknowledge each other’s contributions. These discourse and facilitation moves help to demonstrate that the goal of the discussion – and data analysis in general – is to think deeply about the data and not just to arrive at the right answer.

Mathematics and computational thinking are skills that scientists and engineers use to gain deeper understanding of the phenomenon or problem they are investigating. Supports for a learning orientation frame the purpose of this work as such, rather than as an activity to complete in and of itself, or with the purpose of obtaining the correct answer. Because of varying proficiency in mathematics and computational thinking, supporting students’ learning orientation can help to sustain motivation if or when students struggle with, for example, abstract thinking, logic, or algorithms so that they do not become discouraged by mistakes or incorrect answers. This support may be especially important for students who are concerned that their struggles are confirming negative stereotypes that others may hold about their mathematical and computational ability [see Motivation as a Tool for Equity]. A learning orientation can help students view their mistakes as part of the process of developing mathematics and computational thinking skills in the context of science and engineering.


Have multiple students share out valid, but different, mathematical and/or computational steps for solving a problem to show there are many ways to successfully accomplish the task.
Give students a relationship between two variables that they are studying and ask them to come up with a way to represent that relationship (e.g., thermal energy and particle motion, specifically when thermal energy is transferred to particles, particle speed increases). In sharing out, emphasize the different ways in which students accomplished the same goal.
Have students write, debug, and redo algorithms for problems they are trying to solve as a class or individually.
Engage students in error analysis to figure out what went wrong during computations, where errors were made, and how students might apply their learning from these mistakes to approach similar problems.
Model and then scaffold how to create, explain, and evaluate algorithms or other computational processes. For example, design computational questions or assessments such that they always include an opportunity for students to explain how they arrived at their answer. Provide feedback and/or evaluate these responses based on students’ explanations and not just whether they obtained the correct result.
Use think-alouds to model a learning orientation to students; they can be used to normalize struggle, confusion, and mistakes and to model effective strategies for mathematics and computational thinking.
Be especially mindful of using talk moves to solicit student explanations and respond to student errors so that students do not seek only to produce the right answer and do not attribute their mistakes to ability/intelligence.

A learning orientation helps convey the important understanding that there are multiple ways to construct explanations and design solutions, rather than a single right answer that the teacher is seeking. Exploring different solutions and explanations is a part of the process of learning engineering and science. The goal is for students to be thinking deeply and meaningfully about the how and why of phenomena or problems, rather than merely completing an explanation or design as a classroom task. A learning orientation helps students feel comfortable with sharing explanations and design solutions at an early, potentially underdeveloped phase and helps students to be receptive to feedback geared toward improving their work. When students discuss alternative explanations and design solutions with their peers, a learning orientation supports the perspective that the purpose of discussion is to create better explanations and design solutions.


Demonstrate a commitment to the process of sense-making in relation to explanations by:

  • Asking open-ended questions and asking students to support their claims with evidence using the language of science (see talk moves)
  • Providing tools/scaffolds/structures to support sense-making (e.g., consistent tools for helping students construct and evaluate Claim-Evidence-Reasoning statements across units).[ ] Scaffolds should give general guidance (e.g., “You should explain why the phenomenon occurred”) as well as guidance specific to the explanation they are currently working on (e.g., “You should explain why the salt and ice mixture was able to freeze pure water.”); be detailed enough to help students but not so detailed that students ignore the help; and should fade over time
  • Modeling sense-making during more teacher-led demonstrations or presentations of information to develop a greater understanding of a phenomenon (e.g., think-alouds while explaining how a variable or variables relate to another variable or a set of variables, describing how to judge the appropriateness of the claim, evidence, and/or reasoning and how to articulate reasoning for making this judgment)
  • Actively communicating the value and scientific authenticity of revising explanations and providing opportunities for students to revise their explanations based on new evidence and more developed understanding of phenomena
Demonstrate a commitment to the process of sense-making in relation to design solutions by:
  • Eliciting students’ ideas of how to define the problem
  • Providing ample time for students to engage in an iterative and systematic process of generating, testing, and improving their solutions
Use small group work to allow students to discuss initial ideas and explanations and then share out group responses to the whole class. This might help decrease feelings of social comparison for students who are unsure about their explanations.
A jigsaw protocol can give students a sense of personal responsibility for generating explanations or design solutions and reinforce the idea that multiple explanations or design solutions, supported by evidence, are possible. The expert groups can work collaboratively to generate an explanation or design solution, and then students can share out and evaluate the different explanations/design solutions in their jigsaw groups.
Give students opportunities to construct explanations and design solutions early in a unit, and then revisit and revise these explanations and solutions throughout the unit as students acquire more knowledge.
When explanations or design solutions are visible (e.g., in writing or on chart paper), do a gallery walk or other share-out with structure (e.g., sentence stems or a note-taking guide) to help students observe and reflect on how peers’ explanations or design solutions are different without judging which one is “best”/“right.” Conclude by asking students to reflect on what they’ve learned/how their own understanding has changed/what new questions they have after viewing others’ explanations or design solutions.

The purpose of argumentation in science and engineering is to come to consensus on explanations, models, data analysis, interpretations, and other artifacts of engaging in science and engineering practices. When students are the authors of these artifacts, they can perceive arguments about their work and ideas as a critique of them personally or a judgment on their intelligence, especially if they worry about confirming negative stereotypes that others may hold about their scientific ability [see Motivation as a Tool for Equity]. A learning orientation helps students see that argumentation is focused on reaching consensus about ideas (i.e., reaching a shared understanding of a phenomenon or design problem) rather than judging an individual or the individual’s ideas. Argumentation requires that students listen to each others’ evidence and ideas, which could lead them to reflect on and revise their own ideas or choose other supporting evidence. Having a learning orientation sets up students to be open to adjusting their own explanations/models/interpretations/designs based on others’ arguments to improve their understanding of a phenomenon or optimization of a design solution.


Whether in writing or discussion, individually or in groups, have students provide evidence and reasoning for multiple sides of an argument, as well as for counterarguments and changing arguments, in order to emphasize that there are numerous explanations, models, investigation methods, and approaches to data analysis and that they can be revised over time in light of new information about a phenomenon or design problem.
A whole-class activity like Four Corners or a continuum could support students articulating multiple arguments/dimensions of an argument by taking a stance (e.g., strongly agree, agree, disagree, strongly disagree) and then explaining their evidence and reasoning to try to persuade others. It would also provide students an opportunity to hear multiple perspectives during a classroom activity and ask questions of their peers, build off of their arguments, or change their own mind about which argument is best supported by evidence. Support students in respectfully identifying strengths and weaknesses of their peers’ claims during this activity
  • Some “why” questions that can be asked to help students support their claims:
    • What evidence do you have?
    • What scientific ideas support your claim?
    • Why do you agree or disagree? What are your reasons? What is your evidence?
    • What could be some other possible claims? Do you have evidence?
    • Do you agree with the points being made? Why?
    • Who has a different opinion? What is it? How is it different?
    • Why are you using that as evidence and not the other data? How would your claim change if you used all the data?
    • How is that idea related to what was previously discussed? What reasons do you have for saying that?
Introduce and practice teacher and student talk moves and sentence stems that make requesting and providing evidence/reasons a routine practice in the classroom and focus attention on the ideas rather than the ability, intelligence, or status of the students sharing them.
Model for students the process of offering an evidence-based argument around understanding phenomena or solving problems, receiving feedback and responses (from students), and modifying the original argument to demonstrate how to engage in argumentation with a learning orientation and normalize the practice of having ideas critiqued.
Use descriptive, criteria-based rubrics to evaluate oral and written arguments to help students better understand the components of persuasive argumentation and effective supporting evidence and avoid focusing on whether their argument is “good,” “right,” or high-scoring.
Use a fishbowl discussion to allow some students to practice making and defending arguments while other students observe and evaluate the arguments (and potentially any talk moves that students are practicing using) and provide feedback to the discussants. Make sure to rotate groups so that students get practice in both roles.
After discussions or writing assignments where students have presented and defended arguments, explanations, or ideas, routinely schedule in reflection time for students to think about and explain where they have landed in their thinking, extending the practice of argumentation to private reflection and synthesis as students develop a greater understanding of a phenomenon or identify optimal characteristics from a set of design solutions. Then, bring closure to an argument where students reconcile their differing ideas so that they can decide on next steps as a class. Whether or not students are able to reach consensus, ask them questions like “What is our best explanation at this point?” or “Who has changed their thinking?” in order to promote the practice that argumentation involves working together to achieve a greater shared understanding.

A learning orientation is important to help students actively process and think critically about the information they are obtaining, evaluating, and communicating in service of figuring out phenomena or solving design problems. Students with an ego orientation or who are concerned about confirming negative ability stereotypes can be prone to using shallow learning strategies to “just get by” and avoid looking incompetent, especially when they lack confidence in their skills [see Motivation as a Tool for Equity]. Enacting this practice effectively should be less about the rote regurgitation of information that lends itself to shallow engagement and more about using higher-order thinking to obtain, evaluate, and communicate information. Supporting students’ learning orientation is important to ensure that students engage in information-seeking and communication for the purpose of sense-making and developing competence, rather than for task completion, points, or trying to look smart or avoid looking less capable than other students.


Teach and encourage the use of active reading strategies when evaluating information to communicate that comprehending scientific texts is a difficult task that can be accomplished through effective strategy use.
Consider having students work in groups to understand and evaluate the content presented in readings and then communicate the content to classmates (e.g., through a jigsaw). This places the emphasis on working together to gain a thorough understanding of the text, rather than certain students being the fastest readers, or in the “best/highest” reading group.
Have students share work (written work, oral presentations) with each other so that they can see that there are multiple ways of obtaining, evaluating, and communicating information (consider using a gallery walk or other share out-structure). Provide sentence stems, descriptive rubrics, and other structures to support students giving each other constructive feedback to improve the work (e.g., claims being made without substantial evidence, observations are presented but the implications tied to the observations are unclear/not discussed, inferences are made in lieu of data) rather than merely praising or dismissing it as “good” or “bad.” At the end, ask students to reflect on what they’ve learned/how their own understanding of a phenomenon or design problem has changed/what new questions they have after observing others’ work.
Use anonymous pieces of student work as models to show different ways of communicating scientific information. Identify choices that students made in orally, verbally, or visually communicating scientific information.