FCAT Science Standard Arianna Medina

SC.8.N.1.6 (Science, 8th grade, Nature of Science, Lesson 1, Chapter 6) Understand that scientific investigations involve the collection of relevant empirical evidence, the use of logical reasoning, and the application of imagination in devising hypotheses, predictions, explanations and models to make sense of the collected evidence.

Collecting Relevant Empirical Evidence Empirical Cycle Empirical cycle Is the cycle that you must go through when collecting empirical evidence in an experiment and this cycle consists of following stages: Observation Observation is the collecting and organizing empirical facts to form hypothesis Induction Induction is the process of forming hypothesis Deduction Deduct consequences with newly gained empirical data Testing Test the hypothesis with new empirical data Evaluation Perform evaluation of outcome of testing

Logical Reasoning Logic has you thinking with reason and arguments. The use of logic shows the relationship of the parts of an idea to the whole idea. For example, you can see a relationship between a few trees and the entire forest. The scientific method is a rational, logical thought process that is used to figure out facts and truths. All of the answers must be able to be proved. To scientists, the truth is something that is quantitative (Fact based; able to be proved) Instead of qualitative (Opinion Based).

Logical Reasoning (Inductive .vs. Deductive) There are two types of logical reasoning, Inductive Reasoning and Deductive Reasoning. Deductive Reasoning Deductive reasoning has you starting with information or an idea that is called a premise. Eventually you come up with conclusions that are based on your original premise. Here's a way to think of it, (1) If this happens...(2) and this happens...(3) then you can come to this conclusion. If the premises are true, then your conclusion should also be true. Inductive Reasoning Inductive reasoning works in the opposite direction. You start by having a number of observations. It is a process in two parts. First you start with specifics and come up with a theory. When you apply that theory to new areas, it is inductive reasoning. You organize data into categories and say, "What do these have in common?" There is a problem with inductive reasoning: your conclusions have more information than the facts you use. You start with dozens of observed examples, take an inductive leap, and assume millions of possible examples. If the conclusion is true, then new premises and assumptions are true.

Predictions The hypothesis is your general statement of how you think the scientific phenomenon in question works. Your prediction lets you get specific. The experiment that you will design is done to test the prediction. An important thing to remember is that once you develop a hypothesis and a prediction, you shouldn't change it, even if the results of your experiment show that you were wrong. An incorrect prediction does NOT mean that you "failed." It just means that the experiment brought some new facts to light that maybe you hadn't thought about before. The judges at your science fair will not take points off simply because your results don't match up with your hypothesis.

Using Models Models allow us to investigate complex things that we don’t understand well by using our knowledge of simpler things. Once a model finds supporting evidence and is accepted, it can be confidently used to make reliable predictions about the phenomenon it represents. Finding a model that fits a phenomenon is what we mean by “explaining” or “understanding” that phenomenon. Once models are accepted, they allow scientists to communicate and understand each other because they provide a common, shared mental picture of a phenomenon. And models are not the end products of scientific inquiry. They usually generate ideas for new models that can be tested, helping scientific knowledge to advance.