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. If students do not feel confident that they can ask questions and define problems successfully, they are less likely to put effort into these tasks that are key to engaging meaningfully in authentic scientific inquiry and engineering design. In order to be able to successfully implement activities aimed at answering questions and finding design solutions, it is important to build students’ confidence by providing clear directions, explaining the phenomenon or design scenario, and providing supports to help students ask questions and define problems that are calibrated to their current level of understanding and skill. Providing informational feedback supports students in further developing their skill at asking questions and defining problems.
- One way to introduce these questions is to have students practice by asking questions about a phenomenon or design problem that is familiar to them
Models are a reflection of a scientist’s or engineer’s current understanding of a system. Students will have varying levels of understanding throughout a learning sequence in which they develop and generate a representation of a target phenomenon or design problem, use and describe its relationships and interactions, and evaluate and determine its limitations and explanations. Throughout this process it is imperative to support students’ confidence in developing, using, and evaluating a model as they move from potentially naive understanding to more sophisticated understanding of a system. Students may also lack prior experience engaging in scientific or engineering modeling practices, as they may not have encountered this in previous science classes. Science and engineering teachers, therefore, have an important role to play in supporting the confidence of students in learning this particular practice.
Students may have little experience with planning, carrying out, and evaluating investigations and with the specialized equipment needed to investigate particular phenomena or test design solutions. Investigations also contain many steps and therefore many places where students may encounter challenges. Supporting students’ confidence as they engage in these activities will be crucial for them to feel comfortable proceeding from planning to completing an investigation. At the same time, the complexity and safety risks of some investigations could make teachers prone to over-scaffold, which could reduce students’ confidence by diluting the level of challenge and communicating feelings of distrust. It is therefore important for teachers to balance adequate supports with sufficient challenge in order for students to build confidence in this practice.
- identifying multiple variables, such as independent and dependent variables and controls;
- selecting tools needed for data collection;
- determining how measurements will be taken and logged; and,
- deciding how many data points are sufficient for supporting a claim; provide time for students to reflect on the process and their progress on achieving each mini-goal) so they can focus on one part at a time and provide informational feedback on how their plans are aligning with the objective for the investigation. As students gain competence in planning parts of an investigation, give them larger chunks at a time to plan.
There is likely a wide variety of math ability levels in a single science class. Differences in skill may require different levels of scaffolding in order to develop confidence for all students. Some students may have little experience with data or may have limited confidence in successfully being able to tabulate, graph, or perform statistical analysis on data. Students may also be uncomfortable presenting the results of the analysis and interpretation to their peers. Supporting students’ confidence as they engage in these activities will be crucial for them to feel comfortable working with data.
- Guidelines for graphing: a checklist for the parts of a graph, thinking guides for students to determine a good scale for the data they are graphing or the type of graph that will be most useful for their purpose
- Guidelines for data tabulation: checklists for how to set up a frequency table, how to set up a table for the different variables in an experiment, etc.
- Guidelines for summarizing data: different summary statistics (e.g., mean, median, mode) and what information they provide scientists and engineers
Students may have little experience using mathematics and computational thinking to represent, model, and analyze variables and their relationships to make sense of phenomena or solve design problems. Students’ mathematical and computational thinking proficiency and, more importantly, their confidence in those abilities may vary widely. Ample examples, models, and opportunities for success are crucial to support students who may enter science class with lower confidence in these areas and for those students whose skills can be developed further. Informational feedback will help all students understand when they are progressing and, if they are not, what they can work on to improve.
- Guidelines for graphing: the parts of a graph; how to determine a good scale for the data they are graphing; what type of graph will be most useful for their purpose
- Spreadsheets for algorithms:
- Functions in Excel or Google Sheets (e.g., calculating the mean or sum of several numbers; looking up numbers or text in a data set)
- Examples can help demonstrate to students what an algorithm is
- Process charts for algorithms:
- Common logical structures (e.g., if, then, else; for loop; while loop)
- Examples of simple algorithms that can be used as building blocks or jumping off points
Constructing an explanation requires students to use several skills at once to articulate a claim, select and present supporting evidence and science knowledge, and support the claim using logical reasoning. Some students may be less familiar or comfortable with the norms and practices of constructing explanations. Each student will have a different skill level and comfort level in each of the skills and practices needed to construct an explanation and in being able to use those skills in concert to create an explanation. Providing clear description and expectations of an explanation task and supporting, encouraging, and giving informational feedback to students as they develop these skills helps students to improve in constructing explanations without becoming overly frustrated or thinking they cannot do it. When properly structured and scaffolded, constructing explanations can build students’ confidence by reaffirming and building on what they already know. Similarly, designing solutions requires the iterative application of several skills to arrive at a design solution and benefits from the support, encouragement, and feedback promoted by this design principle.
- Some scaffolding examples:
- Here is my claim [... we believe that X is caused by ... or we believe that Y has a role in how Z happens ...]
- If this claim or explanation is true, then when I look at this data, I would expect to see [this particular result or this outcome]
- The reason I’d expect to see this is because I collected data from a situation that is really close to the real thing we are studying, and if we had these outcomes, it would mean that [state a brief causal chain of events—this chain has to be consistent with known science ideas/facts]
- We did see the data pattern we expected. We believe this supports our claim
- If our claim was not true, then I’d expect to see [a different set of patterns in the data or a particular outcome]. But we didn’t see that outcome, so this reasoning also supports our claim
- There may be other explanations for the data, such as ______ or ______, but this does not seem likely because __________
Explicitly teach the qualities of a successful explanation and how to improve preliminary explanations (e.g., determine whether and describe why the claim, evidence, and/or reasoning are/are not appropriate or valid), then use those same qualities to provide encouraging and informational feedback when students are sharing their own explanations.
- 1(2011). Supporting Grade 5-8 Students in Constructing Explanations in Science: The Claim, Evidence, and Reasoning Framework for Talk and Writing (1st ed.). Boston: Pearson..
Some students may lack confidence to engage in argumentation, especially if they feel unsure of their own science and engineering understanding. Teachers can combat this lack of confidence by helping students understand the goals and expectations of argumentation and in supporting students throughout the process of developing and making an argument with guidance and informational feedback. Showing students that strategies can help them compose effective arguments can also help build their confidence in this practice. Finally, careful attention to the specificity of the informational feedback students receive when competing arguments are considered and evaluated is critical to supporting students’ confidence in argumentation.
- Create tools to support common tasks (e.g., graphic organizers for Claim-Evidence-Reasoning) and make them consistently available to students. This can help make challenging tasks more accessible
- Use board space or anchor charts to ensure that the central question is clear and to record and sort points of agreement and disagreement as the students move toward reconciliation in their argument
- Provide options for level of challenge so students can select the level that suits them. For example, allow students to decide whether or not they need a Claim-Evidence-Reasoning graphic organizer later in the school year
Reading comprehension and synthesis can be difficult for many students, and they may lack confidence as readers. In particular, scientific readings, especially NGSS-based readings, can be difficult, quite long, and formatted differently than traditional textbooks (e.g., main ideas may not be in bold face or in pull-out boxes). Understanding and evaluating the information in these readings may require a different process from what students are used to. Providing students with multiple strategies for identifying big ideas, main points, and potential flaws in reasoning, as well as annotating text effectively for future communication is important for students’ confidence as they try to understand these challenging texts. Students may also feel uncertain that they can effectively communicate new information about phenomena or design problems when they lack confidence in their own scientific understanding.
- Set norms where students have guidelines to follow for engaging in discussion – e.g., each student has a chance to speak, must offer at least one piece of evidence for their conclusions about scientific and technical texts. Provide opportunities for students to communicate their understanding in a variety of ways