Full Circle: A Strategy to Keep Learner Programs Moving

More on component-composite analysis, examples, and real-life application

Here is the important, second half of my first post on component analysis.

A composite is a larger skill that is produced from two or more smaller component skills. Basically, a skill made up of other skills. It’s a blending of all the mastered, component skills before it. The interesting phenomenon here is that nearly every skill can be a component skill and a composite skill at the same time. Every skill is made up of components while also being a component of the next, more advanced, composite skill.

Let’s try a few real life analogies. Pizza, for example. Pizza consists of: pepperoni, cheese, dough, and sauce. These ingredients are part of the pizza—they are the components to the pizza. The pizza is a composite of those ingredients.

Now let’s zoom out a bit further. Pizza is also a component to something larger than itself, namely a pizzeria. Pizzerias consist of many components: chairs, tables, people eating, breadsticks, and…pizza. See below for more examples, and note that an item can have multiple composites.

Ok, enough with the analogies. Let’s talk about how component-composite analysis is going to help us come up with a game plan for coming up with goals and/or troubleshooting them.

Let’s go with Candyland (again). Let’s pretend we want to teach Candyland. Starting with identifying the component skills of Candyland, we might decide on the following: matching colors, sitting for five minutes, moving a game piece down a line or path, turn taking, etc. Again, component skills are the skills that make up the ability to play Candyland.

Now for the composite part. Candyland is also a smaller component to something larger and more developed. When you’re coming up with these larger composites, you’re thinking of the next generation of that skill. What’s version 2.0? What’s a more evolved iteration of my target? What does my target look like with increased response effort? What is a skill that might consist of all the skills necessary for Candyland, but require just a little bit more?

Let’s think of a skill that includes most of the skills that Candyland requires, in addition to a few others. How about the board game Sorry!? It requires many of the same component skills: turn taking, card flipping, moving a game piece down a track, sitting, scanning, etc. Its also consists of a few other, more advanced skills that aren’t present in Candyland. For example, in Sorry!, one has to understand counting spaces and moving multiple game pieces (as opposed to just one). One could argue that Sorry! is a composite of Candyland and that Candyland is a component of Sorry! You might consider focusing on Sorry! once your learner has demonstrated fluency with Candyland.

Check out the graphic below for further examples of other programs to target.

You’ll note that the composite skills are slight iterations or advancements on the target skill. Ultimately, the target skill is a component skill (or at least a logical prerequisite) of its composite skill.

A few things you can do now:

• The composite part of component-composite analysis helps keep skills moving once they’ve hit mastery. Look at your learner’s programs that have been mastered or are approaching mastery. Consider teaching their composite skills.

• Try it for yourself! Pick a goal that you’re considering and list out the component and composite skills for that goal. Do this often. You’ll begin to recognize a complex network that exists between so many of the skills we target.

• Forward this article on to your RBTs and supervisees—it might increase instructional ideas. By teaching them how instructional design works, it will increase their involvement in the direction of their learners.

• Read my previous two posts on tool skills and composite analysis. Both articles function as primer for this one.

• Again, I recommend The Morningside Model of Generative Instruction: What It Means to Leave No Child Behind by Kent Johnson and Elizabeth Street.

Johnson, K. & Street, E.M. (2004). The Morningside Model of Generative Instruction: What It Means to Leave No Child Behind (1st ed.). Cambridge Center for Behavioral Studies.