Next Generation Science Standards 101: Practicing the Practices (And what the heck that means for the non-Science Houses of STEM!) (Part One)

If you're as deeply involved in science education research as I am, it's more than likely that you're already aware of the Next Generation Science Standards (NGSS)--at least of their general existence.

If you're more involved in the act of science education itself (in a classroom, at home, maybe in a library) and not so much in reading 400 page documents on your Tuesday night, the NGSS might be completely new to you. 

Wherever you are on the spectrum of understanding, I'm here to help you move closer to comfortable with the Standards. 

I began my "official schooling" in science education just a couple months after the first draft of the Standards was made public.

Together with a professor one semester from retirement and a class of six other blank-slate Teacher-Hopefuls (some of whom have gone on to be amazingly successful classroom teachers), we waded through the entirety of Earth and Space Systems standards. We spent every day engaged in active discussion and exploration of what an NGSS-aligned classroom would look like in comparison to the science classroom we had all known and experienced.

As the NGSS have developed and evolved over the last six years, I have been lucky enough to evolve beside them (I even took that class again four years later to discover more about the developments). 

My teaching philosophy always favored active learning, rather than passive learning--especially passive learning in the form of listening to lectures, copying notes, and half-heartedly scanning textbooks for homework answers. 

The Framework for K-12 Science Education (the 400 page document that brought the NGSS to fruition) and the NGSS themselves provided the language needed to transform all science learning into active learning. Which brings us to our first vocabulary word for the day: Three-Dimensional Learning.

Three-Dimensional Learning, as detailed by The Framework, is composed of--well--three learning dimension in science education:

1. Science and Engineering* Practices
2. Disciplinary Core Ideas
3. Cross-Cutting Concepts
   
   

(*We'll dive into the Engineering part later. For now, we're going to stay focused on science.)

In the absolute simplest terms, the Practices describe how students will explore the Ideas and the Concepts that bridge those Ideas. Stay with me here, because this is super important: a successful science education comes from standards, curriculum, instruction, and assessment that incorporate all three dimensions. 

I chose to begin our adventure into the NGSS and Three-Dimensional Learning with the Science and Engineering Practices deliberately and for a simple reason: they are the most important shift in modern science education.

Simply put, the Practices are the knowledge and skills that are required to do work in science. The Practices move us away from learning about science, to learning by doing science. Perhaps you don't quite have phenomena frames down yet (or even know what those are), but you should at least be striving to provide experiences for your learners to practice their Practices.

Of course, no one is expected to become an expert overnight, I know for many of you, this is your first exposure to all of this language. So I promise we're going to go over it slowly over the next few blog posts. For now, we're going to focus on the Practices.

Already feeling pretty comfortable practicing the Practices? Scroll on down to the bottom of this post for a quick refresher, then meet me over in the next classroom for NGSS 102: Building Bridges With Cross-Cutting Concepts!

Simply put, the Practices are the knowledge and skills that are required to do work in science. It doesn't matter what that science content is (the Ideas and Concepts), learners need to be able to implement the Practices to do that science. This is one of the aspects of Three-Dimensional Learning that makes it particularly relevant to any type of science educator. Whether you are a classroom teacher, a homeschool parent, a librarian, a play-group leader, you can craft experiences that allow your learners to practice their Practices!

"Oh my goodness, Emily. You keep talking about these 'Practices,' but you haven't told us what they are yet!"

I know, I know. But it is so freaking important for you to understand the background and intentions of the Practices within the framework of Three-Dimensional Learning. The Practices keep our learners doing science! 

Without any further ado, I present to you the eight Science and Engineering* Practices:

(Psst...Just a reminder that we'll be tackling the distinction between Science and Engineering in a later post. For now, I'm going to narrow this discussion down to the science side of things.)

1. ASKING QUESTIONS

​It is no coincidence that Asking Questions is the first Practice we're going to unpack. After all, questions are the engine that drives science. Developing and refining learner's questioning skills is critical to moving forward in the scientific process.

At the earliest stages, our focus needs to be on helping learners develop the scientific habit of asking questions about the world. Teach your learners how to tap into the reservoir of curiosity inside all of us. Of course, once the habit of asking questions is formed, it's time to start refining those questions.

The first crucial step in refining questions is enabling your learner to distinguish between a scientific and a nonscientific question. For example, "How does a hot-air balloon driver control the craft's altitude?" is a very scientific question. It is a question that can be answered and tested through the scientific process. "Why are hot air balloons the transportation of choice in steampunk alter-worlds?" while a very valid question, is decidedly not a scientific question.

When boiled down to their simplest form, scientific questions are variations of four distinct and basic questions:

• What exists?
• What happens?
• Why does it happen?
• How do we know?

Learners then build upon these basic skills to begin asking questions that are more relevant, focused, and sophisticated. Questions about texts they read and phenomena they observe. Questions that require empirical evidence to answer. Questions that challenge the premise of an argument. Questions that seek to refine models and understanding. 

2. DEVELOPING AND USING MODELS

Ah, here we are again, facing down a new vocabulary word. (Or perhaps it's not new at all, and you are a modeling pro, in which case you should promptly pat yourself on the back and then keep reading. Never know when you might learn something new.)

A model, simply put, is a representation of some sort of phenomenon. For example, the poster on your wall featuring a cross-section of Earth or a cross-section of a flower are structural models. They provide a representation of the structure of Earth and the structure of a flower.

Aside from diagrams, models can take the form of replicas, analogies, simulations--some models are even mathematical. *Mind. Blown.*

This is one of those topics that I think is easier to see than read. Luckily, Bozeman Science has a great set of video resources on all of the practices. Here are Paul Anderson's thoughts on the Practice of Developing and Using Models. 

Regardless of what kind of STEM educator you are (formal, informal, aspiring), modeling is one Practice in particular that needs to be addressed explicitly--at least occasionally. It's important to have some form of formal lesson on modeling that allows learners to explore the concept of modeling and to evaluate what exactly it is that they're creating.

Beyond creating models, learners should also have chances to use models to simulate phenomenon. 
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So, if you and your learners build a model of the moon, the sun, and Earth, don't stop at building! Keep your learners interacting with the model. Give them guidance and opportunity to manipulate the model to show how phenomena occur. How do the phases of the moon happen? Can your learner move the pieces of the model to demonstrate each phase?

Once your learners gain comfort developing and using models, and establish their foundation of understanding of modeling as a concept, it's time to begin honing the Practice. Learners should be able to create and interact with more refined and more abstract models as their understanding develops. 

We'll spend more time on models later--I have waaaaay more to say on the topic than I could possibly fit here. For now, suffice it to say that I am a firm believer in the power of developing and using models to solidify and expand a learner's understanding of a concept.

3. PLANNING AND CARRYING OUT INVESTIGATIONS

In scientific investigations, learners extend their scientific questions--you know, those testable questions we discussed in Practice 1--by first considering how they can be tested. Often these investigations follow the Scientific Method (especially early in the development of this practice) to guide learners from their questions to acceptable answers.

Let's consider the bubble blowing activity I use to guide preschool learners through the scientific method.  

We start with a cup filled halfway with water and a straw, and then we work through unpacking the steps of the scientific method. They observe bubbles being blown into the cup and then use those observations to ask questions. (I've done this activity with dozens of preschool learners and, let me tell you, kids are all about the giant bubbles!)

Once we all have our questions, the learners are challenged with developing a hypothesis--a testable answer to their question. In the case of the giant bubbles, a common hypothesis is that blowing harder into the straw will make bigger bubbles--which is a freaking perfect hypothesis! It can be easily tested with the materials we have on hand through an experiment.

Which brings us to a great opportunity to explicitly practice Practice 3 by planning and carrying out bubble-blowing investigations.

This might take some prompting when you're learners are getting started. Have them consider how they can test their hypothesis. A popular answer here is to blow bubbles as hard as they can. But,of course, if we only blow bubbles hard, do we really know if the size changes? So learners then consider how we can find out if blowing harder makes bigger bubbles, such as by blowing softer. This usually leads to a three-part experiment where we blow into the straw softly, normally, and strongly. 

During the process, learners take time to write notes about the results they see--the data--they will look over--analyze--in order to form their answers--conclusions. 

Grab a free PDF download of the worksheet I use with preschoolers to high schoolers while we work through the scientific method!

Once learners are comfortable with planning and carrying out investigations, it's time to start--you guessed it--refining the practice. Learners should begin to explore how they can get better data to answer their questions. There's two important aspects of "better" to be aware of: accuracy (how close the data is to the right answer) and precision (how close the data points are to each other).

One of the simplest ways to begin refining the accuracy and precision of investigations to have learners consider what makes an appropriate sample size. Going back to the bubble experiment, we decided three data points were all we needed to make an accurate enough conclusion. When larger scope questions are being explored, though, larger sample sizes will often be needed. So how do we go about changing investigations to improve data?

Before we go any further, there are three very important vocabulary words we should address: independent variables, dependent variables, and controls. 

Anything we are measuring in an investigation are variables. Independent variables are, well independent, meaning they don't change because of other variables. Dependent variables, then, do vary depending on the other variables. Controls are the variables that are kept constant during an investigation so that they don't interfere with the variables we are trying to measure.
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Quiz time! Consider the bubble experiment one more time. Is blowing strength an independent or dependent variable? What about bubble size--independent or dependent? And what about the type of liquid? The size of the cup? The size of the straw? 

Got your answers? Let's compare notes!

• Independent Variable - Blowing Strength
• Dependent Variable - Bubble Size
• Controlled Variables - Liquid Type, Cup Size, Straw Size

​​Learners should get better and better at identifying variables, as well as figuring out how they can be measured, changed, or controlled. 

Controls are particularly important here! Controlled variables allow other scientists to replicate the experiment, which is how the science community verifies the work. If other scientists conduct the same experiment with the same controlled variables, they should be able to get the same results. Of course, that doesn't always happen...

So how do we improve our learners ability to plan and carry out investigations? Let them practice it!

Let go and let them have at it! (Important note: Please take any and all safety precautions and remain aware of your learners.) But seriously, let them get dirty and make mistakes. From each and every one of those mistakes, they will learn a new lesson on how to plan more accurate and precise investigations.

​When they finish one investigation, encourage them to consider how they might improve it! This practice of repeating the investigations is called iteration. It is through this process of repetition and refinement that scientific discoveries are made.

Ending with one last reference to the bubble experiment: I always ended our activity with having the learners offer at least one way they could change the experiment to get better answers. One lively seven-year-old promptly dug out straws of different sizes and requested a cup of every drink they had in the fridge. Let me tell you, he's doing science right!

4. ANALYZING AND INTERPRETING DATA

The data that we get from scientific investigations have little meaning until we begin to analyze and interpret the data. 

One of the most common ways scientists analyze and interpret data is by creating tables and graphs that present the data in a visual format that allows patterns to be more easily recognized. Tables allow investigators to summarize all of their data--whether its a small body of data or quite large--in a format that is conveniently accessible and easily navigable. Graphs, on the other hand, summarize data visually, allowing more complex relationships to become visible. Statistical analysis expresses relationships in data sets using mathematics. 

Each method of analyzing data has its own limits and benefits. Learners that are able to utilize a variety of methods to analyze and interpret one data set are able to form more connections and develop a deeper understanding of the relationships between variables.

Let's take a quick meander back to the bubbles. With my preschool-level learners, we created a table that displayed qualitative data.

While the use of qualitative data, rather than quantitative data, limited our ability to use statistical analysis, learners were able to translate their tables in graphs.

As with the other Practices, learners will continue to refine their skills to take on more sophisticated data sets and analytical techniques. Learners should be given ample opportunities to explore large data sets--such as those available in internet databases--and identify correlations. 

The Library has a great resource exploring Real-Life Data in the Climate Sciences. ​

The activities are particularly suitable for middle school to post-high school learners--of course, you know your learners best and the guided workbook might provide just the challenge your more advanced learners need.

Want to learn more about computer-aided data interpretation? Sign up to get early access to a free course that will make you an expert (at least on the basics)!