NGSS ConnectionsIn 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.
Asking questions and defining problems drives science and engineering. Scientific questions arise from the curiosity of a researcher, predictions of a model, or findings from previous investigations. Engineering design problems arise from an unmet need or desire. Ultimately, however, the decision of which question to answer or problem to solve arises from the scientist or engineer. For students to engage in authentic scientific inquiry and engineering design, they must experience a sense of autonomy over the questions and problems they attempt to answer and solve. The constraints that a typical science teacher must navigate do not always allow teachers to provide complete autonomy over the science questions and engineering problems that students work on. However, by supporting student autonomy in asking questions, teachers can give students opportunities to exercise agency in their scientific inquiry and engineering designs that reflect authentic practice.
Developing models involves reflection and opportunities for evaluation and iteration, which requires students to make decisions and direct the modeling process in order to understand a phenomenon or solve a design problem. It is important that students have the autonomy to make choices about their models that are consequential to their science learning and to the representation of scientific phenomena (e.g., inclusion of mechanisms, components of a system, representations of components, or relationships that can be used to explain or predict phenomena), rather than merely making choices about surface features of the model (color, size, materials, etc.). Additionally, multiple representations of the same phenomenon or design problem can be valid, so promoting students’ autonomous model development is critical to authentic scientific and engineering practice.
The goal of an investigation is to “figure something out.” Authentic investigative experiences require sufficient student agency to make sense of phenomena or design solutions to problems, ask new questions, and explore ideas of interest; and provide sufficient opportunities for cognitive autonomy so that students are engaged in the “figuring out.” Creating these conditions could take the form of supporting student ownership of the investigation’s purpose and next steps by encouraging students to generate ideas or questions about a phenomenon or design problem to drive the investigation. Developing the skills to plan investigations requires student autonomy to design procedures to accomplish a certain objective. Even when the investigation is a little more pre-determined because of students’ age, skill level, or safety concerns, autonomy can be supported by prompting students to think through the rationale for the investigation procedures. The safety risks of some investigations may mean that teachers must dictate specific constraints on what is possible in the lab, limiting full student control over how to conduct an investigation, but it is important to find opportunities to support other types of student autonomy in these situations.
- Big ideas (BI) person. This person pulls the group (occasionally) back to the scientific purpose of the activity. (Often a group will get too wrapped up in the rote execution of the directions)
- Clarifier. This is a role of monitoring everyone’s comprehension about one or two key science terms related to the investigation
- Questioner. This person asks probing questions during the activity, listens for questions posed by other group members, and then revoices the questions to make sure that the whole group takes a moment to hear and entertain questions from everyone
- Skeptic. This person tries to strengthen the group’s work by probing for weaknesses in the developing investigation
- Progress monitor. This person asks others to periodically take the measure of the group’s progress
Cognitive autonomy is especially important to encourage students to make their own decisions about how to analyze or make sense of the data, as well as to generate alternative interpretations and explanations. Working with data might make teachers prone to undermine student autonomy if they suggest that there is a clear “right” answer, such as a predetermined set of similarities and differences between two data tables that the teacher is leading students to identify. There might also tend to be an overemphasis on smaller autonomy allowances (e.g., letting students choose the colors for a graph) without accompanying demands on students’ cognitive autonomy in making sense of phenomena or problem solving. It is important to provide sufficient time and scaffolding for students to engage in rigorous, autonomous sense-making through the analysis and interpretation of data.
Problems requiring the application of mathematics and computational thinking often have multiple possible solutions or multiple possible algorithms to reach the optimal solution. When feasible, students should be given the autonomy to choose how they will approach a problem and how they will calculate a solution. Autonomy can be undermined if students feel there is only one correct answer or that they are being asked to follow a predetermined set of steps.
Constructing an explanation relies heavily on student-centered learning (i.e., students thinking on their own and engaging in sense-making). Student choice and decision-making are implicated in the act of defining problems and proposing solutions. It is also important that student ideas and thinking drive the explanations and design solutions they are generating and developing over time, whether those explanations and design solutions are occurring during
Autonomy is critical for students to be able to engage meaningfully in authentic scientific argumentation to make sense of phenomena or solve design problems. Students need adequate time and opportunity to generate and revise claims, gather evidence, justify their ideas, and evaluate their own arguments against other possibilities. Additionally, providing students with a rationale for why argumentation is a key practice in science and engineering is an important way to support their sense of autonomy in selecting evidence and constructing and evaluating arguments.
Information can be obtained, evaluated, and communicated in multiple ways. It is important to support students’ autonomy throughout these processes to be sure that students feel a sense of agency and ownership over their science and engineering learning and the ways in which they obtain, evaluate, and communicate science and engineering information to others. Autonomy in this practice also entails asking students to rationalize their choices and think deeply about how their choices are related to deepening their understanding of phenomena or solving design problems. Autonomy is essential to the process of evaluating evidence and being able to present information as scientifically sound or as an “optimal” design in engineering.