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How to Process & Apply Knowledge in Science

Instructor: Amanda Robb

Amanda holds a Masters in Science from Tufts Medical School in Cellular and Molecular Physiology. She has taught high school Biology and Physics for 8 years.

In this lesson you'll be learning about analytical skills that will help you become a better scientist. Here, you'll learn how observing, making comparisons and inferences, generalizing, and applying data can help you reach scientific conclusions.

Why Is Science Important?

How did the solar system form? Why are trees green? Will there be a cure for cancer? All these questions fall under the domain of science. In science, we investigate the natural world, asking questions, making observations, and gathering data. But how do we interpret that data and make meaningful conclusions? Data doesn't mean much if we can't understand and apply it. Today, we're going to be learning some steps to analyze and apply your scientific knowledge. Through observations, research, and analysis, you'll be able to come to scientific conclusions on your own.

Making Observations

The first step in figuring out any scientific problem is to make observations. An observation is anything you can notice about the subject. For example, if you were trying to find out what the best material is for creating a parachute, you might start by making observations. What are important characteristics of a parachute? Should they be strong, flexible, light weight?

Making observations is the first step in applying scientific research
observations

Accessing Prior Knowledge and Research

Once you've looked at the problem, it's time to get into the gritty work of research. In order to design the best parachute, you're going to need to know what's already out there. Using scientific sources like text books and technical articles, you'll be able to research specific categories of knowledge. Dividing your findings into known categories, such as research about momentum, force, or kinematics will help you organize your thoughts. Do you want to investigate one category, or a link between two? Categorization is a way to organize your research and results.

Making Inferences to Design Experiments

Once you have all your research done, you can use that information to make a prediction. If circular shapes are used, would an elliptical shape work better? Should the circle be larger? To answer your question, you not only need to know what's currently being done, but be able to apply how you could make it better. Let's look at our parachute example.

You know that parachutes work by creating air resistance to counteract gravity. Through your research, you've found that increasing the surface area of the parachute increases air resistance. How does this apply to your project? What could you change about your parachute to make it better?

Now's the time for application. Since a larger surface area increases air resistance, and air resistance makes parachutes better, you can infer that if you make your parachute larger, it will work better. An inference is a conclusion based on evidence and reasoning. You had some information from your research - that's your evidence. You transferred that knowledge to designing your own experiment. The research didn't tell you to test a larger parachute size, but you were able to infer that information.

These inferences help you make generalizations, or applying a known fact to multiple situations. You don't know explicitly that increasing surface area will help your parachute, but you know this works in other situations. You generalize this information to apply it to your own research.

Students use inferences to design and carry out experiments
experiments

Making Conclusions

Once you've collected your data, what do you do with it? Like designing the experiment, you have to analyze the factual information you have and make inferences to develop a conclusion. Let's go back to our parachute example.

Let's say you get your data and notice that as parachutes increase in surface area, the time to land increases. But, this is only true to a point. You notice that at a certain size, the parachutes actually take less time to land. What should you make of this data?

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