In this segment, we outline the eight science and engineering practices of chemistry. Students also discuss qualitative and quantitative observations.
Host outlines eight science and engineering practices of chemistry. Teacher and students discuss qualitative and quantitative observations. Students are challenged to come up three questions for what caused the Ogeechee River fish kill in 2011.
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. (NRC Framework, 2012, p. 61-62)
Asking Questions and Defining Problems
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. (NRC Framework 2012, p. 56)
Constructing Explanations and Designing Solutions
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.”(NRC Framework, 2012, p. 52)
Engaging in Argument from Evidence
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. (NRC Framework, 2012, p. 73)
Generating a Hypothesis and Developing a Model
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. (NRC Framework, 2012, p. 58)
Obtaining, Evaluating and Communicating Information
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. (NRC Framework, 2012, p. 76)
Planning and Carrying Out Investigations
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. (NRC Framework, 2012, p. 61)
Using Mathematics and Computational Thinking
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. (NRC Framework, 2012, p. 65)
constant - also known as the controlled variable, any factor that is kept the same during an experiment.
hypothesis - a tentative explanation or prediction that can be tested by further investigation.
manipulated variable - also know as the independent variable, the one factor that changes within an experimental group.
meniscus - the curved surface at the top of the liquid in a tube.
model - a physical, conceptual, or mathematical representation of a real phenomenon whose purpose is to explain and predict what happens in real life.
observation - any information gathered using any of your five senses or lab instruments.
qualitative data - measurements that do not include numbers.
quantitative data - measurements that include numbers.
replication - data collected by different teams from samples gathered at the same location.
responding variable - also known as the dependent variable, the variable that is being measured as a result of the experiment.
significant figures - a term that represents the precision of a measurement.
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