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Automaticity: It's Automatic

Have you ever found that you've made your way home—by car or mass transit—with little or no memory of actually taking the journey?

If you have, you've likely experienced automaticity: the ability to perform an action, or sequence of actions, without conscious thought. Our brains go on "automatic pilot" when an activity is so familiar to us that we can do it without thinking about it. This is why experienced drivers on a familiar route can find their way home while their brain is occupied by the events of the day or plans for tomorrow.

The same phenomenon happens in the classroom. Achieving automaticity in foundational skills and cognitive processes is essential for effective and efficient learning across all content areas. Here's a closer look at how we achieve automaticity, why it matters, and how Thinking Maps can help.

What We Mean By Automaticity

Benjamin Bloom defined automaticity as the ability to perform an action or skill "unconsciously, with speed and accuracy, while consciously carrying on other brain functions." When we achieve automaticity with a skill, we no longer have to think about each individual step in the process. Instead, we can simply do it, while simultaneously thinking about something else.

Think again about our driving example. For new drivers, the mechanics of handling the car are difficult and require intense concentration. Where was that turn signal again? What am I supposed to do when the light turns yellow? As we become more experienced with driving, these basic skills become automatic. Instead of thinking "lift up on turn signal with left hand…look over right shoulder…turn wheel slightly…" we can smoothly change lanes with little effort.

The hallmarks of automaticity are speed (the ability to perform the action or activate the skill quickly), effortlessness (the task feels easy and does not require much concentration), autonomy (the process occurs without deliberate activation on the part of the thinker), and unconsciousness (the thinker is not fully aware of the processes he/she is engaged in). Our brains rely on these automatic processes for all kinds of activities, from touch-typing to riding a bike.

In the classroom, we want students to achieve automaticity in the basic skills that underlie a complex process. In reading, this includes skills such as word decoding and recognition. In math, we want students to achieve automaticity with basic computation. Achieving automaticity in these basic skills is a necessary prerequisite to fluency: the ability to perform a complex activity (such as reading) smoothly, easily, and with a high level of skill.

Freeing the Brain for Higher-Order Thinking

Automaticity is a critical component of learning. When we achieve automaticity with lower-level skills, we free up the brain to engage in more complex forms of thinking. Going back to the driving analogy, experienced drivers are safer drivers in large part because less of their brain is taken up by the mundane mechanics of operating the car. This allows them to use their brainpower on more important things—like noticing and reacting to a car suddenly shifting into their lane or a child running into the street.

To understand why, we need to look at the concept of cognitive load. Cognitive load refers to the total amount of working memory we are using when we perform a task. Working memory is the part of the brain that is responsible for short-term information processing while we are performing a task. Our working memory has limited capacity; it can only hold so much information at a time and can't perform very many tasks simultaneously. That's why it's hard for new drivers to pay attention to where they are while they're thinking, "Wait, how do I shift gears again?"

When we achieve automaticity with a skill, it no longer takes up working memory. It is happening somewhere else in the brain entirely. That means we can now use our working memory for higher-order tasks.

We see this at work clearly in the development of literacy. When students are using a lot of mental energy to decode words, they don't have much left over to focus on the meaning of what they are reading. As decoding and word recognition become automatic, they are able to read for comprehension. The same basic process happens in math and other content areas.

The Road to Automaticity

How does a skill become automatic? It's like the old joke about how you get to Carnegie Hall…practice, practice, practice.

The more we perform a skill, the more automatic it becomes. Deliberate, focused practice, with plenty of repetition, helps us achieve automaticity.

This means continuing practice beyond mastery—a process sometimes called overtraining. In overtraining, you continue to practice even after you are able to demonstrate mastery on a task. For example, a professional violinist doesn’t stop practicing a piece the first time they are able to play it through correctly. They continue to play the piece until they feel like they could "play it in their sleep" to ensure that their playing is not only technically correct but also effortless, smooth, and fluent.

Overtraining also helps students achieve automaticity in the classroom. For best results, practice should be consistent and coherent, so students don't have to relearn the "rules" of the task each time. At the same time, there needs to be enough novelty and flexibility in the practice tasks to avoid boredom. This can be achieved by having students perform the same skill in a variety of contexts—for example, learning new sight words by reading many different types of stories with the same sight word list.

Building Fluency in Cognitive Processes

Thinking Maps builds automaticity and fluency in accessing and applying key cognitive processes, including Defining, Describing, Comparing and Contrasting, Classifying, Whole-to-Part Relationships, Sequencing, Cause and Effect, and Analogies and Relationships. These are the core cognitive processes that underlie learning across all content areas.

One of the keys to the efficacy of Thinking Maps is that students use and apply the Maps across all content areas and grade levels. Because they are using the same type of Map each time they need to activate a specific cognitive process, their use becomes automatic and effortless.

This is different from using a range of different "graphic organizers" to complete similar tasks. This approach requires students to reinvent the wheel every time they need to activate a thinking process. Using the same set of Maps each time (e.g., Tree Maps for classifying, and Flow Maps for sequencing) allows students to spend less time figuring out how to organize their thinking and more time thinking deeply about the content itself. In this way, Thinking Maps reduces the overall cognitive load and makes learning more efficient.

As students achieve automaticity with the Maps, they gain fluency in using the cognitive processes for deep comprehension and analysis. In fact, many students use the Maps automatically when they need to analyze complex content or solve a problem—even if creating a Map is not an explicit part of the assignment. When we see students take ownership of the Maps in this way, we know they have mastered the higher-order thinking processes behind them.

Download Our White Paper for More!

Want to know more about brain-based learning? Download our white paper: The Building Blocks of Brain-Based Learning—The Research Base for Thinking Maps. You'll learn:

  • How the brain processes, filters, stores, and retrieves information
  • The six building blocks of brain-based learning
  • How Thinking Maps taps into the way we are already wired to learn

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