Understanding cognitive learning theory
Have you ever wondered why it is so hard to remember people’s names? Or why it can be just as hard to remember a long list of things? Or why you can sometimes remember the gist of story but not the details?
The way that we consume, process, and remember information is the focus of cognitive learning theory. Over the last 50 years, cognitive researchers have learned an astounding amount about the way the human mind manages the information it is exposed to. We know how information moves into the mind, how it is represented, how it is recalled or forgotten, how it is transformed or distorted.
As L&D professionals, we operate in an information-centered profession. All instruction involves information – presenting it, having people interact with it, having people think about it, etc. Regardless of how we conceive of the act of teaching, it cannot be done without information. To be the best possible L&D practitioner requires that we become familiar with the core tenets offered by cognitivism.
What is cognitive learning theory in a nutshell?
Cognitive learning theory is a collection of somewhat independent theories and sub-theories that collectively hold that the mind is an information processing device that collects, manipulates, and stores information in ways similar to a computer. It’s not necessarily that the mind is a computer but more that the computer offers a useful analogy for understanding and talking about how the mind operates. Input, process, output.
Broadly speaking, the cognitive sciences are concerned with:
- How information gets from the world into our minds
- What form that information takes in our minds
- How we store and retrieve the information
- How we mentally manipulate and change the information
- How we express the information
What is learning according to cognitive learning theory?
From a cognitive learning theory perspective, learning occurs when we take information from the external world, bring it into our mental space, process it appropriately, produce whatever output is intended, and retain our ability to do the same thing again in the future when called upon.
There are three distinguishing features to note:
- The object of learning (and all mental activity) is information.
Information, in any of its various forms (verbal, visual, auditory, etc.), sits at the center of learning. Information is perceived, collected, moved around, manipulated, and expressed. This is cognition. Without information, there would be nothing to process and no mental activity would occur. Neither information nor mental activity can exist without the other.
- Cognition and learning take place in the mind.
In contrast to behaviorism, which limits itself to observable behavior, and constructivism, which is focused on social context, cognitive learning theory is singularly focused on what happens in the mind. Action is a consequence of thought – behavior is caused by thinking. Knowledge and action are not the same thing. There is the one. And then there is the other. Notably, in this view, learning could feasibly take place without any visible evidence. In cognitivism, it’s not of any particular importance whether or not learning is expressed.
- There is a hardware component and software component.
In this view of learning, there is information (the software) and processing equipment (the mind) which acts on it. Just like a computer, the hardware has limits, capacities, and protocols that must be followed. In order for learning and cognition to occur, information must be processed within the natural constraints of the hardware. One of the important implications of this rather simple model is that creating effective learning requires two major focuses of analysis: the information and the human mind, with its natural processing protocols and limits.
What are its philosophical roots?
Cognitive learning theory, like behaviorism, is an objectivist learning theory. This means that it presumes there is an objective world that exists outside of our minds. That every person may interpret the outside world a little differently does not change the fact that there is a material world and it is what it is, at least from the objectivist point of view.
This sits in contrast to relativistic theories like constructivism, which posit that the true meaning of things is relative and thus that there is no true meaning or reality outside of the mind. There is no absolute truth in this viewpoint, but instead only individual constructions of meaning.
This is important to know because it has implications for how a theory views goal setting, instruction, and assessments. Objectivist approaches presume learners can get things right or wrong. Success and failure – and all shades in between – are things that can be measured and managed. Relativist theories are inclined to view goals, truth, and right/wrong as individual constructions that cannot be objectively judged.
How do the mechanics work?
In cognitive learning theory, the way that we learn varies depending on what it is that we are trying to learn. For example, how we learn facts differs from the way we learn concepts, or processes, etc. Hence, there is no single learning process that captures everything (this is in part where conditions-based instructional design models come from).
However, all of the various learning processes operate within the same basic perception and memory structures. These are like the hardware, or the laws of physics that all learning is constrained by. All learning, no matter the nature of the thing being learned, must conform to these laws, specifically, the laws of memory.
Memory: the basic parts
The human memory system has three parts: sensory registers, short-term memory, and long-term memory. Information passes through each part in sequence on its way to becoming integrated into our minds.
Part 1: Sensory registers
At any given moment, our senses are being exposed to more information than our minds can process. Our sensory registers help us decide what information to pay attention to by holding the information until we can assign meaning to certain parts of it. The rest is instantly discarded very quickly. This happens unconsciously.
Part 2: Short-term memory
Information that has been assigned meaning moves into short-term memory. While there, we commit some information to long-term memory and discard the rest. Once it has been discarded, it is no longer available to us. Information in short-term memory memory remains available to us longer than in the sensory registers, but still only a brief 15-seconds or so on average.
Part 3: Long-term memory
Whereas nothing stays in short-term memory, long-term memory is where information goes to live permanently. Once information lands in the long-term memory store, it is there for good, though you must have mechanisms for retrieving it.
How information goes from the world into long-term memory
From the cognitive perspective, the goal of learning is to get information from the world into long-term memory and back again. There is an understood path that information follows enroute to this destination.
- It is perceived by the senses and enters into the sensory registers.
When something is picked up by the senses, it is not necessarily noticed. It is merely available to be noticed. What gets noticed is affected by your goals and other such things at a conscious and subconscious level.
- It enters into short-term memory
Once something is noticed, it enters into your awareness and your short-term memory. Once there, it can be discarded or given your attention. It will remain in short-term memory as long as you give it your attention or until you exceed the capacity of short-term memory by adding additional things into STM. Most information that enters short-term memory is lost. STM can hold no more than seven units of meaning (plus or minus two) at any given time.
- It is “encoded” into long-term memory.
In order for information to move from short-term memory to long-term memory, it must be associated with something already in long-term memory. This is referred to as encoding. It is usually a conscious process, though passive encoding is possible.
- It is retrieved using the encoded cues.
The information is retrieved on command by using the item that was already in long-term memory as a trigger for recalling the more recently added bit of information. In other words, the association between the old and new units of information is used to trigger recall.
In what form is information stored?
When information enters into our sensory registers, it is stored ever so temporarily in its raw form, meaning it looks in our minds just like it does in the real world. Before it moves into STM, we have assigned meaning to certain parts of the information (e.g. that thing is a tree). For example, when the letter “A” enters into our sensory registers, it is not a letter but a jumble of random lines. It does not become the letter “A” until we assign it that meaning.
Once the meaning has been assigned, it is the meaning that is stored in STM and subsequently in LTM, not the details of the information as it was originally perceived. When you tell a story, the listener will not be able to remember the words you used, but will be able to retell the story with a high level of accuracy using different words. Bottom line: we remember meaning, not the exact physical attributes of information.
Once meaning enters into LTM, it becomes integrated into a pre-existing schema or mental model. Schemas are structures that we hold in long-term memory that serve as organizers for certain types of information. For example, we may have a schema for the physiologic anatomy of our bodies. When we learn something new about, say, our biceps, it becomes part of our body schema. In this way, when new meaning enters into LTM, it is transformed by our existing schema and it also transforms the schema. Relating this to the encoding and retrieval process, the schema becomes the thing that allows movement from STM to LTM – it is the association to existing LTM information needed for long-term memory storage. We can move things from STM into LTM without pre-existing schemas, but it requires making random associations (e.g. using mnemonics, methods like the memory palace, etc.), which are far weaker retrieval cues.
Concerning the type of information that gets processed, this is actually a complicated subject worthy of its own book. Generally speaking, the same processes, rules, and limits apply whether it be visual, auditory, and verbal/text information that we are processing. Visual and verbal information are processed in parallel channels that can either compliment or conflict with one another. But generally speaking, cognition is fundamentally the same across information types.
What are the implications for the design of instruction?
In terms of practical application, this well defined architecture of the human memory system offers a number of essential lessons for instruction. Here are some of the big ones:
1. Prime learners to ensure they notice important information.
Every moment of our lives, we’re bombarded with more stimuli than we can process. Our sensory registers quickly discard everything without relevance or meaning before we are even aware of it. In order to make sure our learners notice what we want them to notice (and don’t unintentionally overlook important things), we need to:
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- Reduce noise and increase signal in our instructional materials/environments
- Point out or emphasizing the things that need noticing
- Give learners a goal or task that primes them to give meaning to relevant data
2. Associate new things with familiar things.
In order for people to incorporate new things into long-term memory, they need to associate the new things with items that are already stored in LTM. The obvious implication here is that we need to connect the things we are teaching to things that our learners already know, whether that means drawing upon their experiences, using analogies and metaphors, or other devices.
3. Associate new things with schema.
While it can work to draw associations between new things and random familiar things (e.g. associating a management concept with a particular person you know), it is most effective if you can associate them with an existing schema. If you are teaching a new management concept to people leaders, whether or not they realize it, your learners already have pre-existing schema about management. You want to associate these new concepts with their existing schema by helping them invoke prior experiences and relating the new ideas to them.
4. If people do not have existing schema, create them.
If learners do not already have an existing schema in long-term memory, begin by helping them create one. In practice, this means providing them with an overarching organizing framework in which the learner can situate the new things they are learning. Advance organizers, done properly, can help with this.
5. Lead with the old, then add the new.
For as simple as this concept is, it is one of the most impactful. Yet it is also one of the most rarely practiced. When we are making the association between the old and the new, always lead with the old. Instead of explaining a concept followed by examples, give examples and then explain the concept. Instead of explaining a new management concept and then relating it to a learner’s prior experience, invoke the learner’s prior experience and then related the new idea to it.
6. Do not overload people with too much information.
There is not enough space here to cover all of the practical tactics you can use to work within and around the natural limits of our memory systems. Yet these are some of the most important and impactful practices. For now, it should be sufficient to emphasize that you should avoid overloading learners systems by never presenting them with more information than STM can hold at any one time (seven plus or minus two), allowing learners time to consolidate information (i.e. transition information from STM into LTM), and providing mental breaks to allow their memory systems to reset.
What are the implications for reinforcement and coaching?
Cognitive learning theory does seem well suited to offering much guidance for reinforcement and coaching. Cognitivism as a theory is focused on what happens in the mind, whereas coaching in particular is focused on overt behaviors. Furthermore, cognitivism does not fully address the strength of associations that are created during instruction. It instead seems to imply that once something is integrated into a schema it remains there ready to be retrieved. It does acknowledge that the associations made during instruction can decay, but its remedy for this is limited to just re-rehearsing those associations. It views the problem as an informational one. Finally, cognitivism does not have robust theory in the area of motivation, rewards, and punishment. Thus, cognitivism is most useful in guiding us on how to design initial instruction.
Notable thinkers and researchers
Conclusion
Thinking of human mental activity as an information processing endeavor may not seem reflective of what it is like to think and behave. But there is no question that information is a critical part of how we think, live, and learn. We read books and articles. We listen to podcasts and radio. We watch TV and movies. All of these these things are undoubtedly informational. Do we never learn from such things? Are we not affected by them at all? Do they not contribute to what we think of us our knowledge bases?
Whether or not we want to describe the entirety of the learning experience as fundamentally about processing information, there can be no doubt that information plays a role in virtually all instruction. We use PowerPoints. We assign articles and case studies. We create charts, diagrams, and other visuals. We speak using human-created language. Every time we do any of these things, we give learners information that they must process if they hope to use these materials to gain new capabilities. That in turn means that when we include information like this in our instruction, we need to do so in accordance with the way our learners’ minds process that information.
Cognitivism offers an extraordinarily robust and highly practical framework for understanding not just how people learn, but how they think in general. This overview article provides a small fraction of the practical lessons to be had from cognitivism.