Great Ideas from the Brain Sciences: Our Human Cognitive Architecture

Great Ideas from the Brain Sciences: Our Human Cognitive Architecture

By: Mirela C. C. Ramacciotti

In architecture, inner workings matter more than what the eyes can see. It is no different in our heads. What we see in the learner’s production—their learning behavior—is sometimes a fragment of what we don’t see but is happening inwardly in a constant, messy way. Rest assured that the messy part is not on you—this is on the inextricable relation between nature and nurture—but this “mess” needs orchestrating and that is when teachers may step in.

An illustration that metaphorically depicts the brain as a city.

But let’s break this into steps. Starting with you, teacher: Have you noticed that sometimes you say something that you have no idea you knew? Fast forward to your classroom, how often have you noticed that students seem to emulate—sometimes totally unaware—the greetings (a personal favorite, “hi, dears”), fillers (like “”hmm” “well,” and “ah”), and even the occasional expletive (“gosh” or “damn it”) you might have overused (without even noticing). Well, this can be explained, and it has to do with how learning takes place even—or mostly, should I say—when learners are not aware of it.

A photo of Edward C. Tolman
A diagram of an elevated maze.

Back in the 1930s, a psychologist named Edward Chace Tolman was interested in knowing how external features were internalized without any need for reward.  To that end, he worked with rats, and mazes. He devised ways to understand how we pick up information from the environment, internalize it, and display it—sometimes much later—when the need arises. He gave a name to this process of internalization: cognitive maps, taken to mean how we mentally represent the signals (e.g., words, objects, places) we gather from our context. For instance, as a teacher, you may intentionally make a point of using the phrase: “Excuse-me, can you repeat that, please?” in the English language learning environment very early on, when students are not even aware of how many words there are in this string. Students get the gist (conveyed by your gestures, most likely) and repeat to you whatever they originally said. After a short while, they will most probably be repeating that sentence back to you or to a peer without you having to “teach” it explicitly. This happened, most often, because they have listened to it many times over; they have understood when to use it, and as soon as the proper context arose, they showed you (and themselves) that they had processed the information that was intentionally present in the context and learned it—not even being aware of the fact. In cognitive terms, they have built up their knowledge repertoire and cemented useful information, in the form of a cognitive map, for later usage. This is latent learning and, as a teacher, you have orchestrated the inward learning of a very useful chunk.

Now let’s consider a different scenario: Recall how many times you had to explicitly teach the word “please” in the adult language classroom. I bet that you are having a hard time recollecting any. That is, most probably, because you are an excellent and polite user of the language and have used that same word so many times that students did not have to be prompted to insert it in their speech. Most likely, to you, it became evident that your students had properly learned how to use “please” whenever the situation ensued; and to them, it seemed just the natural thing to do. Implicit learning has taken place. In other words, by being exposed to a usage pattern concerning the word “please”—that to you was not a “learning goal” but just part of who you are and how you act—students unconsciously learned it and used the word when the need arose. Notice that here not being conscious of the input nor intentional about its use is key as the process becomes automatic, or one where knowledge has become tacit.

A photo of Arthur S. Reber
The cover of "Implicit Learning and Tacit Knowledge"

Our understanding that we acquire new knowledge through experience (repetition) without being conscious of it (implicit learning) came about through the work of Arthur S. Reber in 1967. He devised an experiment, in the field of cognitive psychology and linguistics, where subjects had to study a set of letter strings generated by a falsely random (yet very complex) set of artificial grammar rules. After the testing period (when subjects were “learning” without being conscious of it), they had to say if the letter strings violated the rules or not. The interesting thing is that they gave the right answers but could not say why. In other words, subjects showed that they learned the rules of the artificial grammar without knowing them. Going back to the example of “please” in the classroom, imagine how many words, structures, patterns your students have been learning without being aware of it. Teachers are truly powerful architects of learning.

Let’s see what happens when blueprints are joined with tools. The analogy here is with human cognitive architecture and learning skills. And the underlying concept is that of cognitive load. John Sweller, in the 1980s, noticed that a certain amount of information could be learned without conscious effort as it demanded the use of domain-general skills (like thinking and listening) whereas academic information (reading, writing, and arithmetic, for instance) needed explicit teaching and domain-specific skills that call on learners’ working memory. Thus, conscious effort in learning translates into a burden on learners’ working memory—a cognitive load.

A photo of John Sweller

Now, learning how to read and write meaningfully, especially in another language, is a demanding task in and of itself. Imagine if the teacher does not know how to plan instruction so that this effort, plus the load represented by the learning materials, overwhelms students? This is cognitive overload and may cause stress and reduce the probability of learning. To avoid this, teachers’ architecting skills should be employed towards the use of worked examples (especially important for novice learners where instructional guidance is explicitly given) and away from inquiry/discovery-based learning. Teachers should also steer away from over-explaining things (the redundancy effect) or splitting information that should be delivered together (the split-attention effect) by planning well what to say and how to present information in advance. In the end, Sweller’s words (see video) make a lot of sense: “Without an understanding of human cognitive architecture, instruction is blind.”

Further Reading

Cognitive maps in rats and men
In this classic 1948 article, Edward C. Tolman challenges behaviorist views with his theory
of cognitive maps. Through experiments with rats in mazes, he argues for goal-directed
learning and mental representation—paving the way for cognitive psychology. The article
can be found here.

Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55(4), 189–208.

Implicit learning and tacit knowledge: An essay on the cognitive unconscious.

Arthur S. Reber explores how individuals unconsciously acquire complex knowledge structures. This foundational paper examines how implicit learning operates independently
of conscious awareness, contributing to our understanding of intuition and decision-making. 

Reber, A. S. (1993). Implicit learning and tacit knowledge: An essay on the cognitive unconscious. Oxford University Press.

An Introduction to Cognitive Load Theory

This introduction looks at how learning involves constructing new knowledge in working memory and consolidating it into long-term memory.

Emeritus Professor John Sweller, School of Education

John Sweller introduces cognitive load theory in this video, explaining how instructional design can support learning by accounting for the limits of working memory.

Mirela C. C. Ramacciotti is presently engaged as an external lecturer on the topic of Mind, Brain, and Education at the Graduate Level Course with the Psychology Department at the University of São Paulo. She holds a PhD in Neuroscience and Behavior and another in Human Communication Disorders.

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