Projects
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Dimension 1: Practices
Analyzing and interpreting data
Scientific investigations produce data that must be analyzed in order to derive meaning. Because data patterns and trends are not always obvious, scientists use a range of tools—including tabulation, graphical interpretation, visualization, and statistical analysis—to identify the significant features and patterns in the data. Scientists identify sources of error in the investigations and calculate the degree of certainty in the results. Modern technology makes the collection of large data sets much easier, providing secondary sources for analysis.
In the pursuit of scientific discovery, data must be carefully collected and analyzed in order to identify meaningful patterns. To do this, scientists utilize technologies such as tabulation, graphical interpretation, visualization and statistical analysis to assess the significance and accuracy of their findings. With modern technological advancements, collecting large datasets is much more straightforward than before and provides scientists with a variety of secondary resources to draw upon for their studies.
Science
Engineering
Engineering professionals use data collected from tests and experiments to assess how closely a design satisfies specific design criteria. As with scientific research, different tools are needed to identify patterns and interpret results, helping engineers compare various solutions and determine optimum results in relation to constraints.
The Next Generation Science Standards (NGSS) recognize and emphasize the importance of three main dimensions for learning science. These dimensions are essential components in forming each standard—or performance expectation. When taken together, they allow students a chance to gain a more cohesive understanding of science concepts as they progress through their courses.
Three Dimensions of Science Learning
It is important to understand how scientists work in order to make sense of the world around us. The scientific process is a methodical and logical approach to discovering how things in the universe work. It is the foundation upon which all scientific knowledge is built.
The scientific process begins with a question or problem that scientists want to solve. They then gather data and observations about the problem. This data is used to form a hypothesis, which is a proposed explanation for the problem. The hypothesis is then tested through experimentation. If the results of the experiment support the hypothesis, then it becomes a theory. If the results of the experiment do not support the hypothesis, then the hypothesis is rejected and a new hypothesis is formed. This process is repeated until a theory is supported by a large body of evidence.
The scientific process is not always linear. Scientists may go backand revise their understanding due to new evidence or data. The process generally starts with making an observation or asking a question, followed by formulating a hypothesis, conducting experiments and tests to collect data, analyzing the data, and then either accepting or rejecting the hypothesis. If the hypothesis is accepted, scientists create a conclusion. This conclusion is then put out for peer review or further discussion before it is accepted as scientific fact.